Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1, 2, 8, 11 and 15-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 2, 4, 5, 10, 12, 15 and 19 of U.S. Patent No. 10,747,897 B2.
Although the claims at issue are not identical, they are not patentably distinct from each other because while broader the instant application discloses non-patentably distinct limitations as indicated in the table below:
Instant Application 19/256,624
U.S. Patent No. 10,747,897 B2.
1. A privacy policy analysis system, comprising:
a network interface;
one or more processors coupled with the network interface;
a memory accessible to the processor and storing instructions that, when executed by the one or more processors, cause the one or more processors to:
receive a privacy policy associated with a website;
perform a semantic analysis on text of the privacy policy to determine a plurality of privacy policy elements;
determine an element score for one or more of the plurality of privacy policy elements;
generate a privacy policy score from the element scores of the one or more of the plurality of privacy policy elements; and
output the privacy policy score.
2. The privacy policy analysis system of claim 1, wherein:
receiving the privacy policy comprises receiving a website address from a user device; and
the instructions further cause the one or more processors to:
search a privacy policy database for the website address; and
when the website address is present in the privacy policy database, retrieve the privacy policy score from the privacy policy database.
8. A method of analyzing a privacy policy, comprising:
receiving, by a privacy policy analysis system, a privacy policy associated with a website;
performing, by the privacy policy analysis system, a semantic analysis on text of the privacy policy to determine a plurality of privacy policy elements;
determining, by the privacy policy analysis system, an element score for one or more of the plurality of privacy policy elements;
generating, by the privacy policy analysis system, a privacy policy score from the element scores of the one or more of the plurality of privacy policy elements; and
outputting, by the privacy policy analysis system, the privacy policy score.
11. The method of analyzing a privacy policy of claim 8, wherein:
determining the element score for one or more of the plurality of privacy policy elements comprises analyzing language used in each of the plurality of privacy policy elements separately to determine the element score for each element of the plurality of privacy policy elements; and
generating the privacy policy score comprises one or both of combining and interpolating the element scores to determine the privacy policy score.
15. A non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors of a privacy policy analysis system, cause the one or more processors to:
receive a privacy policy associated with a website;
perform a semantic analysis on text of the privacy policy to determine a plurality of privacy policy elements;
determine an element score for one or more of the plurality of privacy policy elements;
generate a privacy policy score from the element scores of the one or more of the plurality of privacy policy elements; and
output the privacy policy score.
16. The non-transitory computer-readable medium of claim 15, wherein:
the privacy policy score is generated based at least in part on user preferences associated with one or more of the plurality of privacy policy elements.
17. The non-transitory computer-readable medium of claim 16, wherein:
the user preferences are associated with a single user.
18. The non-transitory computer-readable medium of claim 16, wherein:
the user preferences are obtained from survey responses from a plurality of users.
19. The non-transitory computer-readable medium of claim 18, wherein the instructions further cause the one or more processors to:
produce a weighting factor for various aspects of privacy policies based on the user preferences, each weighting factor being used to generate the privacy policy score.
20. The non-transitory computer-readable medium of claim 15, wherein:
the plurality of privacy policy elements comprise at least one of a type of data collected, a method used to collect the data, a use for the data, or language used to define a data collection or data usage opt-out policy.
1. A system comprising:
a privacy policy analysis system (PPAS) and a user device, the user device for communicating with websites, wherein each of the PPAS and the user device include:
a processor;
a memory accessible to the processor and storing instructions that, when executed-by the processor, cause the processor to:
automatically determine, at the PPAS, a privacy policy score for a website based on an automatic semantic analysis of text of a privacy policy associated with the website by retrieving the privacy policy score from a database;
receive at the PPAS, from a user at the user device, user preferences that reflect the relative importance of each of one or more privacy policy characteristics to that user;
customize, at the PPAS, the privacy policy score based on the user preferences of that user;
provide, at the PPAS, the privacy policy score to a privacy policy plugin associated with an Internet browser application executing on the user device;
display, at the user device, the privacy policy score within a browser window of the Internet browser application;
block, at the user device, access to the website by the privacy policy plugin associated with the Internet browser application, when the privacy policy score falls below a threshold value; and
survey a plurality of users for receiving, at the PPAS from the plurality of users, user preferences reflecting the relative importance of one or more of the privacy policy characteristics to the plurality of users;
wherein the user preferences received from the plurality of users, are combined to produce a weighting factor for the one or more privacy policy characteristics, in determining the privacy policy score.
2. The system of claim 1, wherein, prior to determining the privacy policy score, the instructions further cause the processor at the PPAS to:
receive a website address from the device;
search a privacy policy database for the website address; and
when the website address is present in the privacy policy database, retrieve the privacy policy score from the privacy policy database.
3. The system of claim 2, wherein, when the website address is not present, the instructions further cause the processor at the PPAS to:
automatically retrieve a privacy policy associated with the website; and
automatically analyze the privacy policy to determine the privacy policy score.
4. The system of claim 1, wherein the instructions to determine the privacy policy score further include instructions that, when executed, cause the processor at the PPAS to:
semantically analyze the text of the privacy policy associated with the website to determine a plurality of privacy policy elements;
determine one or more scores for the plurality of privacy policy elements; and
determine the privacy policy score from the one or more scores.
5. The system of claim 4, wherein the plurality of privacy policy elements include:
types of data collected;
methods used to collect the data;
uses for the data; and
language used to define a data collection or data usage opt-out policy.
6. The system of claim 1, further comprising:
a network interface coupled to the processor and configured to communicate with a network; and wherein the memory further includes instructions that, when executed, cause the processor at the PPAS to:
intercept data from the device, the data including a website address;
determine the privacy policy score of a privacy policy corresponding to the data; and
provide the privacy policy score to the device.
10. A method comprising:
automatically searching a privacy policy database including privacy policy data associated with a plurality of websites to determine a privacy policy score for a privacy policy associated with a website using an identifier, the identifier including at least one of a web site address and a name of an application;
when the privacy policy score is found, retrieving the privacy policy score associated with the identifier;
when the privacy policy score is not found, retrieving text of the privacy policy from the website and automatically semantically analyzing the text of the privacy policy to determine the privacy policy score;
receiving, from a user, user preferences that reflect the relative importance to that user of each of a plurality of privacy policy characteristics;
customizing the privacy policy score based on the user preferences of that user;
providing the privacy policy score to a privacy policy plugin associated with an Internet browser application executing on a device;
displaying, at the device, the privacy policy score within a browser window of the Internet browser application;
blocking, at the device, access to the website by the privacy policy plugin associated with the Internet browser application, when the privacy policy score falls below a threshold value; and
surveying a plurality of users for receiving, from the plurality of users, user preferences reflecting the relative importance of one or more of the privacy policy characteristics to the plurality of users;
wherein the user preferences received from the plurality of users, are combined to produce a weighting factor for the plurality of privacy policy characteristics in determining the privacy policy score.
11. The method of claim 10, further comprising:
receiving data that includes a uniform resource locator (URL) for the website; and
wherein the privacy policy score is determined in response to receiving the data.
12. The method of claim 10, wherein automatically analyzing the retrieved privacy policy comprises:
semantically analyzing text of the retrieved privacy policy to determine a plurality of privacy policy elements;
determine one or more scores for the plurality of privacy policy elements; and
determine the privacy policy score from the one or more scores.
15. A memory device comprising instructions that, when executed, cause a processor to:
determine a privacy policy score corresponding to one of a website and an application by searching a privacy policy database including a plurality of privacy policy scores and associated text of privacy policies, each privacy policy score corresponding to one of a website and an application;
when the privacy policy score is not present in the privacy policy database:
automatically retrieve text of a privacy policy corresponding to one of the website and the application from a data source when the privacy policy score is not present in the privacy policy database;
automatically determine one or more scores associated with sections of the text of the privacy policy by semantically analyzing text of the privacy policy to determine a plurality of privacy policy elements and determining a score for each of the plurality of privacy policy elements; and
determine the privacy policy score based on the one or more scores;
receive, from a user, user preferences that reflect the relative importance of a plurality of privacy policy characteristics to that user;
customize the determined privacy policy score based on the user preferences of that user;
survey a plurality of users for receiving, from the plurality of users, user preferences reflecting the relative importance of one or more of the privacy policy characteristics to the plurality of users;
wherein the user preferences received from the plurality of users, are combined to produce a weighting factor for the plurality of privacy policy characteristics in determining the privacy policy score;
provide the privacy policy score to a privacy policy plugin associated with an Internet browser application executing on a device;
display, at the device, the privacy policy score within the browser window of the Internet browser application; and
block, at the device, access to the website by the privacy policy plugin associated with the Internet browser application, when the privacy policy score falls below a threshold value.
16. The memory device of claim 15, further comprising instructions that, when executed, cause the processor to determine the privacy policy score in response to receiving data from a device.
17. The memory device of claim 16, wherein the data includes at least one of an identifier of the website and an identifier associated with the application.
18. The memory device of claim 16, further comprising instructions that, when executed, cause the processor to:
determine a change to the privacy policy; and
automatically update the privacy policy score in response to determining the change.
19. The memory device of claim 15, further comprising instructions that, when executed, cause the processor to:
search a privacy policy database for the one of the website and the application; and
when the one is present, retrieve the privacy policy score from the privacy policy database.
Claims 1, 8, 12, 15 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 8 and 15 of U.S. Patent No. 11,790,108 B2.
Although the claims at issue are not identical, they are not patentably distinct from each other because while broader the instant application discloses non-patentably distinct limitations as indicated in the table below:
Instant Application 19/256,624
U.S. Patent No. 11,790,108 B2.
1. A privacy policy analysis system, comprising:
a network interface;
one or more processors coupled with the network interface;
a memory accessible to the processor and storing instructions that, when executed by the one or more processors, cause the one or more processors to:
receive a privacy policy associated with a website;
perform a semantic analysis on text of the privacy policy to determine a plurality of privacy policy elements;
determine an element score for one or more of the plurality of privacy policy elements;
generate a privacy policy score from the element scores of the one or more of the plurality of privacy policy elements; and
output the privacy policy score.
8. A method of analyzing a privacy policy, comprising:
receiving, by a privacy policy analysis system, a privacy policy associated with a website;
performing, by the privacy policy analysis system, a semantic analysis on text of the privacy policy to determine a plurality of privacy policy elements;
determining, by the privacy policy analysis system, an element score for one or more of the plurality of privacy policy elements;
generating, by the privacy policy analysis system, a privacy policy score from the element scores of the one or more of the plurality of privacy policy elements; and
outputting, by the privacy policy analysis system, the privacy policy score.
12. The method of analyzing a privacy policy of claim 8, further comprising:
after generating the privacy policy score, detecting a change in the privacy policy;
processing text of the change in the privacy policy; and
determining an adjusted privacy policy score for the privacy policy based on the text of the change.
15. A non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors of a privacy policy analysis system, cause the one or more processors to:
receive a privacy policy associated with a website;
perform a semantic analysis on text of the privacy policy to determine a plurality of privacy policy elements;
determine an element score for one or more of the plurality of privacy policy elements;
generate a privacy policy score from the element scores of the one or more of the plurality of privacy policy elements; and
output the privacy policy score.
1. A system comprising:
a processor;
a memory accessible to the processor and storing instructions that, when executed by the processor, cause the processor to perform operations including:
automatically determining, at a privacy policy analysis system (PPAS), a privacy policy score for a website based on an automatic semantic analysis of text of a privacy policy associated with the website;
receiving at the PPAS, from a user at a user device, user preferences that reflect a relative importance of at least one of one or more privacy policy characteristics to that user;
customizing, at the PPAS, the privacy policy score based on the user preferences of that user;
determining, at the PPAS, that the privacy policy score is below a threshold value;
blocking, at the user device, access to the website based on the privacy policy score falling below the threshold value;
detecting, at the PPAS, a change in the text of the privacy policy associated with the website after the privacy policy score is determined;
automatically determining, at the PPAS, an updated privacy policy score based on the change in the text of the privacy policy;
customizing, at the PPAS, the updated privacy policy score based on the user preferences of the user;
determining, at the PPAS, that the updated privacy policy score is not below the threshold value; and
unblocking, at the user device, access to the website based on the updated privacy policy score not being below the threshold value.
8. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of a gateway device, including instructions configured to cause one or more data processors to perform operations including:
automatically determining, at a privacy policy analysis system (PPAS), a privacy policy score for a website based on an automatic semantic analysis of text of a privacy policy associated with the website;
receiving at the PPAS, from a user at a user device, user preferences that reflect a relative importance of at least one of one or more privacy policy characteristics to that user;
customizing, at the PPAS, the privacy policy score based on the user preferences of that user;
determining, at the PPAS, that the privacy policy score is below a threshold value;
blocking, at the user device, access to the website based on the privacy policy score falling below the threshold value;
detecting, at the PPAS, a change in the text of the privacy policy associated with the web site after the privacy policy score is determined;
automatically determining, at the PPAS, an updated privacy policy score based on the change in the text of the privacy policy;
customizing, at the PPAS, the updated privacy policy score based on the user preferences of the user;
determining, at the PPAS, that the updated privacy policy score is not below the threshold value; and
unblocking, at the user device, access to the website based on the updated privacy policy score not being below the threshold value.
15. A computer-implemented method, comprising:
automatically determining, at a privacy policy analysis system (PPAS), a privacy policy score for a website based on an automatic semantic analysis of text of a privacy policy associated with the website;
receiving at the PPAS, from a user at a user device, user preferences that reflect a relative importance of at least one of one or more privacy policy characteristics to that user;
customizing, at the PPAS, the privacy policy score based on the user preferences of that user;
determining, at the PPAS, that the privacy policy score is below a threshold value;
blocking, at the user device, access to the website based on the privacy policy score falling below the threshold value;
detecting, at the PPAS, a change in the text of the privacy policy associated with the website after the privacy policy score is determined;
automatically determining, at the PPAS, an updated privacy policy score based on the change in the text of the privacy policy;
customizing, at the PPAS, the updated privacy policy score based on the user preferences of the user;
determining, at the PPAS, that the updated privacy policy score is not below the threshold value; and
unblocking, at the user device, access to the website based on the updated privacy policy score not being below the threshold value.
Claims 8 and 9 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1 and 3 of U.S. Patent No. 12,346,477 B2.
Although the claims at issue are not identical, they are not patentably distinct from each other because while broader the instant application discloses non-patentably distinct limitations as indicated in the table below:
Instant Application 19/256,624
U.S. Patent No. 12,346,477 B2.
8. A method of analyzing a privacy policy, comprising:
receiving, by a privacy policy analysis system, a privacy policy associated with a website;
performing, by the privacy policy analysis system, a semantic analysis on text of the privacy policy to determine a plurality of privacy policy elements;
determining, by the privacy policy analysis system, an element score for one or more of the plurality of privacy policy elements;
generating, by the privacy policy analysis system, a privacy policy score from the element scores of the one or more of the plurality of privacy policy elements; and
outputting, by the privacy policy analysis system, the privacy policy score.
9. The method of analyzing a privacy policy of claim 8, wherein:
determining the element score for one or more of the plurality of privacy policy elements and generating the privacy policy score is done using a machine learning model.
1. A non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors, cause a user device to:
prompt a user of the user device for one or more survey responses for a survey, wherein the one or more survey responses comprise rankings of privacy policy characteristics in order of relative importance, wherein the privacy policy characteristics are related to at least one of data use practices, data collection practices, or opt out provisions of privacy policies;
receive the one or more survey responses from the user;
provide the one or more survey responses to a privacy policy analysis system for use in setting user preferences;
send a request for a privacy policy rating associated with one or both of a website and an application to the privacy policy analysis system;
receive the privacy policy rating, from the privacy policy analysis system, wherein the privacy policy rating is generated based on the user preferences and the relative importance of the privacy policy characteristics from the one or more survey responses of the user and of a plurality of other users that submitted responses to the survey;
present the privacy policy rating on a display of the user device, wherein the privacy policy rating provides a visual indication of privacy risks associated with the one or both of the website and the application;
determine that the privacy policy rating is below a predetermined threshold; and
perform a precautionary action based on determining that the privacy policy rating is below the predetermined threshold, wherein the precautionary action comprises one or both of blocking access to the one or both of the website and the application and providing an alert that the privacy policy rating is below the predetermined threshold.
3. The non-transitory computer-readable medium of claim 1, wherein:
the privacy policy rating comprises a learning algorithm-generated rating.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more.
Step 1: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. The claims recites a privacy policy analysis system, method of analyzing a privacy policy and non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors of a privacy policy analysis system. These are directed to a machine, a series of steps or acts, and a manufacture, and falls within one of the statutory categories of invention. (Step 1: YES).
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
Claim 1, 8 and 15 are directed to an abstract idea because the following claim limitations recite an abstract idea:
A system, method and manufacture comprising :
perform a semantic analysis on text of the privacy policy to determine a plurality of privacy policy elements; (mental process: a human being reading a privacy policy and identifying portions or categories of the privacy policy based upon their meaning);
determine an element score for one or more of the plurality of privacy policy elements; (mental process: a human being evaluating an identified privacy policy element such as phrases, words, etc. and assigning a score to that element .)
generate a privacy policy score from the element scores of the one or more of the plurality of privacy policy elements; (mental process/mathematical concept: combining or evaluating individual scores to determine an overall privacy policy score.)
Claims 1, 8 and 15 recites the following additional elements:
receive a privacy policy associated with a website
output the privacy policy score;
wherein the system is “a privacy policy analysis system”;
a network interface, one or more processors coupled with the network interface; a memory accessible to the processor and storing instructions that, when executed by the one or more processors, cause the one or more processors to(claim 1);
wherein the manufacture is “A non-transitory computer-readable medium having instructions stored thereon that, when executed by one or more processors of a privacy policy analysis system, cause the one or more processors to”
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
The claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with generating and outputting a privacy policy scored based on the evaluation of privacy policy information. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amount to merely receiving the information upon which the abstract analysis is performed, outputting the informational result of the analysis and using computers as a tool to implement the abstract idea. Thus the additional elements are considered mere instruction to apply the abstract idea See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to integrate the abstract idea into a practical application.
Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
One way to determine integration into a practical application is when the claimed invention improves the functioning of a computer or improves another technology or technical field. To evaluate an improvement to a computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. See MPEP 2106.04(d)(1) and 2106.05(a).
Likewise to step 2A prong 2, the claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with generating and outputting a privacy policy scored based on the evaluation of privacy policy information. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amount to merely receiving the information upon which the abstract analysis is performed, outputting the informational result of the analysis and using computers as a tool to implement the abstract idea. Thus the additional elements are considered mere instruction to apply the abstract idea See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to amount to significantly more than the abstract idea itself, even when the additional elements are considered alone and in combination with the abstract idea. (Step 2B: NO).
Therefore, the claims are directed to an abstract idea without significantly more and are unpatentable.
Claim 2
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
Claim 2 are directed to an abstract idea because the following claim limitations recite an abstract idea:
Claim 2 does not recite a new abstract idea.
Claims 2 recites the following additional elements:
receiving the privacy policy comprises receiving a website address from a user device;
search a privacy policy database for the website address; and
when the website address is present in the privacy policy database, retrieve the privacy policy score from the privacy policy database.
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
The claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with retrieving a previously determined privacy policy score corresponding to a website address. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amount to merely receiving identifying information and searching and retrieving stored information using a database. Thus, the additional elements are considered mere instructions to apply the abstract idea using generic computer functionality. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to integrate the abstract idea into a practical application.
Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
One way to determine integration into a practical application is when the claimed invention improves the functioning of a computer or improves another technology or technical field. To evaluate an improvement to a computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. See MPEP 2106.04(d)(1) and 2106.05(a).
Likewise to step 2A prong 2, the claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with retrieving a previously determined privacy policy score corresponding to a website address. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amount to merely receiving identifying information and searching and retrieving stored information using a database. Thus, the additional elements are considered mere instructions to apply the abstract idea using generic computer functionality. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to amount to significantly more than the abstract idea itself, even when the additional elements are considered alone and in combination with the abstract idea. (Step 2B: NO).
Therefore, the claims are directed to an abstract idea without significantly more and are unpatentable.
Claim 3
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
Claim 3 is directed to an abstract idea because the following claim limitations recite an abstract idea:
Claim 3 does not recite a new abstract idea.
Claims 3 recites the following additional elements:
using a web robot to fetch privacy policy text and an associated uniform resource locator (URL) from a plurality of websites.
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
The claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with obtaining privacy policy information that is subsequently analyzed and scored. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely using a web robot as a tool to collect the information upon with the abstract analysis is performed. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to integrate the abstract idea into a practical application.
Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
One way to determine integration into a practical application is when the claimed invention improves the functioning of a computer or improves another technology or technical field. To evaluate an improvement to a computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. See MPEP 2106.04(d)(1) and 2106.05(a).
Likewise to step 2A prong 2, the claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with obtaining privacy policy information that is subsequently analyzed and scored. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely using a web robot as a tool to collect the information upon with the abstract analysis is performed. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to amount to significantly more than the abstract idea itself, even when the additional elements are considered alone and in combination with the abstract idea. (Step 2B: NO).
Therefore, the claims are directed to an abstract idea without significantly more and are unpatentable.
Claim 4 and 5
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
Claims 4 and 5 are directed to an abstract idea because the following claim limitations recite an abstract idea:
Claims 4 and 5 does not recite a new abstract idea.
Claims 4 and 5 recites the following additional elements:
receiving a URL of the privacy policy from a privacy policy score web page visited by a user device..
providing the privacy policy score to the user device.
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
The claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with receiving identifying information for a privacy policy through a webpage and providing the resulting privacy policy score to a user device. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely using a webpage and user device as a tool to receive information used in the abstract analysis and provide the informational result of that analysis. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to integrate the abstract idea into a practical application.
Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
One way to determine integration into a practical application is when the claimed invention improves the functioning of a computer or improves another technology or technical field. To evaluate an improvement to a computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. See MPEP 2106.04(d)(1) and 2106.05(a).
Likewise to step 2A prong 2, the claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with receiving identifying information for a privacy policy through a webpage and providing the resulting privacy policy score to a user device. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely using a webpage and user device as a tool to receive information used in the abstract analysis and provide the informational result of that analysis. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to amount to significantly more than the abstract idea itself, even when the additional elements are considered alone and in combination with the abstract idea. (Step 2B: NO).
Therefore, the claims are directed to an abstract idea without significantly more and are unpatentable.
Claim 9
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
Claim 9 is directed to an abstract idea because the following claim limitations recite an abstract idea:
Claim 9 does not recite a new abstract idea.
Claims 9 recites the following additional elements:
sing a machine learning model to determine the element score and generate the privacy policy score.
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
The claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with determining element scores and generating a privacy policy score. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely using a machine learning model as a tool to implement the abstract scoring process. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to integrate the abstract idea into a practical application.
Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
One way to determine integration into a practical application is when the claimed invention improves the functioning of a computer or improves another technology or technical field. To evaluate an improvement to a computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. See MPEP 2106.04(d)(1) and 2106.05(a).
Likewise to step 2A prong 2, the claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with determining element scores and generating a privacy policy score. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely using a machine learning model as a tool to implement the abstract scoring process. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to amount to significantly more than the abstract idea itself, even when the additional elements are considered alone and in combination with the abstract idea. (Step 2B: NO).
Therefore, the claims are directed to an abstract idea without significantly more and are unpatentable.
Claim 10
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
Claim 10 is directed to an abstract idea because the following claim limitations recite an abstract idea:
Claim 10 does not recite a new abstract idea.
Claims 10 recites the following additional elements:
publishing the score to one or both of a web page and a document.
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
The claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with publishing the informational privacy policy score to a webpage or document. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely using a webpage or document as a tool to present the result of the abstract analysis. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to integrate the abstract idea into a practical application.
Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
One way to determine integration into a practical application is when the claimed invention improves the functioning of a computer or improves another technology or technical field. To evaluate an improvement to a computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. See MPEP 2106.04(d)(1) and 2106.05(a).
Likewise to step 2A prong 2, the claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with publishing the informational privacy policy score to a webpage or document. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely using a webpage or document as a tool to present the result of the abstract analysis. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to amount to significantly more than the abstract idea itself, even when the additional elements are considered alone and in combination with the abstract idea. (Step 2B: NO).
Therefore, the claims are directed to an abstract idea without significantly more and are unpatentable.
Claim 13 and 14
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
Claims 13 and 14 are directed to an abstract idea because the following claim limitations recite an abstract idea:
determining if user preferences exist that are associated with the user; (mental process: a human being determining whether preference information exists for a particular user);
customizing the privacy policy score based at least in part on the user preferences to produce a customized privacy policy score... and the privacy policy score is generated based at least in part on the user preferences.; (mental process: a human being evaluating information according to a user’s preferences or criteria.)
Claims 13 and 14 recites the following additional elements:
the privacy policy is received from a user;
retrieving the user preferences associated with the user;
outputting the customized privacy policy score.
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
The claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with generating or outputting a privacy policy score customized according to user preferences. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely receiving and retrieving information used in the abstract evaluation and outputting the informational results of the abstract evaluation. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to integrate the abstract idea into a practical application.
Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
One way to determine integration into a practical application is when the claimed invention improves the functioning of a computer or improves another technology or technical field. To evaluate an improvement to a computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. See MPEP 2106.04(d)(1) and 2106.05(a).
Likewise to step 2A prong 2, the claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with generating or outputting a privacy policy score customized according to user preferences. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely receiving and retrieving information used in the abstract evaluation and outputting the informational results of the abstract evaluation. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to amount to significantly more than the abstract idea itself, even when the additional elements are considered alone and in combination with the abstract idea. (Step 2B: NO).
Therefore, the claims are directed to an abstract idea without significantly more and are unpatentable.
Claim 18
Step 2A, Prong One: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
Claim 18 is directed to an abstract idea because the following claim limitations recite an abstract idea:
Claim 18 does not recite a new abstract idea.
Claims 18 recites the following additional elements:
the user preferences are obtained from survey responses from a plurality of users..
Step 2A, Prong Two: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
The claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with using preference information obtained from users to generate a privacy policy score. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely gathering the information used in the abstract preference evaluation. Thus, the additional elements are considered mere instructions to apply the abstract idea. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to integrate the abstract idea into a practical application.
Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
One way to determine integration into a practical application is when the claimed invention improves the functioning of a computer or improves another technology or technical field. To evaluate an improvement to a computer or technical field, the specification must set forth an improvement in technology and the claim itself must reflect the disclosed improvement. See MPEP 2106.04(d)(1) and 2106.05(a).
Likewise to step 2A prong 2, the claims fails to achieve a technical solution to a technical problem. Thus the claim fail to provide an improvement to the function of a computer or to a technology itself. The claim culminate with using preference information obtained from users to generate a privacy policy score. See MPEP 2106.04(d)(1) and 2106.05(a). The additional elements are recited at a high level of generality and amounts to merely gathering the information used in the abstract preference evaluation. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES).Therefore, the examiner must find that the claims fail to amount to significantly more than the abstract idea itself, even when the additional elements are considered alone and in combination with the abstract idea. (Step 2B: NO).
Therefore, the claims are directed to an abstract idea without significantly more and are unpatentable.
Claims 6, 7, 11,12,16, 17, 19 and 20
Regarding claims 6, 7, 11,12,16, 17, 19 and 20 the following claim limitations recites an abstract idea
(Claim 6 ) comparing at least one of the plurality of privacy policy elements to pre-scored text to automatically generate the element score for the at least one of the plurality of privacy policy elements. ( mental process: comparing information with previously evaluated information and assigning a corresponding score.)
(Claim 7) process the privacy policy against a set of rules to identify one or both of potentially ambiguous statements and weak statements to assign a preliminary score to the privacy policy, wherein the privacy policy score is at least partially based on the preliminary score. ( mental process: evaluating statements according to predetermined criteria and assigning a rating .)
(Claim 11) determining the element score for one or more of the plurality of privacy policy elements comprises analyzing language used in each of the plurality of privacy policy elements separately to determine the element score for each element of the plurality of privacy policy elements; and generating the privacy policy score comprises one or both of combining and interpolating the element scores to determine the privacy policy score. ( mental process/mathematical concept: evaluating information and mathematically combining the resulting score.)
(Claim 12) detecting a change in the privacy policy; processing text of the change in the privacy policy; and determining an adjusted privacy policy score for the privacy policy based on the text of the change. ( mental process: identifying changed information, evaluating the changed information and revising a prior score based on the identified changes .)
(Claim 16) the privacy policy score is generated based at least in part on user preferences associated with one or more of the plurality of privacy policy elements. ( mental process: evaluating information according to selected preferences or criteria .)
(Claim 17) the user preferences are associated with a single user. ( mental process: limiting the preference criteria used in the evaluation to those of a particular person. .)
(Claim 19) produce a weighting factor for various aspects of privacy policies based on the user preferences, each weighting factor being used to generate the privacy policy score. (mathematical concept: assigning numerical weights to evaluation criteria and using those weights in determining an overall score .)
(Claim 20) the plurality of privacy policy elements comprise at least one of a type of data collected, a method used to collect the data, a use for the data, or language used to define a data collection or data usage opt-out policy. ( mental process: categorizing information according to its subject matter.)
Claims 6, 7, 11,12,16, 17, 19 and 20 recites the additional elements:
Claims 6, 7, 11,12,16, 17, 19 and 20 do not recite any new additional elements different from the ones previously identified in the base claims from which they depend.
Step 2A, Prong 2 and Step 2B
Claims 6, 7, 11,12,16, 17, 19 and 20 fail to recite any new additional elements relative to base claims 1, 8 and 15. Thus, the analysis and findings for step 2A, prong 2 and step 2B incorporates the analysis and findings of claims 1, 8 and 15 however, the analysis and findings includes consideration of claims 1, 8 and 15 as a whole. Therefore, claims 6, 7, 11,12,16, 17, 19 and 20 are directed to an abstract idea without significantly more and is unpatentable
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 7 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
In regards to claim 7, the limitations “potentially ambiguous statements and weak statements” renders the scope of the claim indefinite. Specifically, while the specification states the system may process the privacy policy against a set of rules to identify “potentially ambiguous statements or weak statements” and states the semantic analysis may identify weak statements, ambiguous statements, the specification fails to provide an objective standard for determining when a privacy policy statement constitutes a “weak statement” or is sufficiently capable of ambiguity to constitute a “potentially ambiguous statement.” as the disclosure repeats the use of the terms without defining the boundary of the terms. While the specification does state the policy is processed according to a set of rules this does not cure the issue because the claim does not specify the criteria within the rules that establishes the boundary between a statement that is weak or potentially ambiguous and a statement that is not. As such, the claims are rejected for failing to establish the metes and bounds of “potentially ambiguous statements and weak statements.”
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 6, 8, 9, 11, 15 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over US 20130297626 A1 to Levi et al. (hereinafter “Levi”) in view of US 20140283055 A1 to Zahran et al. (hereinafter “Zahran”)
Claim 1
Levi teaches a privacy policy analysis system, comprising:
a network interface; one or more processors coupled with the network interface; a memory accessible to the processor and storing instructions that, when executed by the one or more processors, [e.g. Levi; Para. 0033 – Levi discloses a legal advisory system 400 (privacy policy analysis system) includes a processor 404 and memory 406, with processor 404 and memory 406 communicating with communication interface 426 (e.g. network interface), local database 424, remote database 428 and user computer 430. ] cause the one or more processors to:
receive a privacy policy associated with a website; [e.g. Levi; Para. 0003-0005, 0019, 0028-0034 – Levi discloses that the system automatically extracts privacy policy information from text in electronic form associated with websites, privacy policy is explicitly identified as a top-level category and system 400 receives text 440 including “text at a website” (e.g. privacy policy text associated with a website.) ]
perform a semantic analysis on text of the privacy policy to determine a plurality of privacy policy elements; [e.g. Levi; Para. 0004-0006, 0018, 0019, 0031-0034 – Levi discloses the system employs machine learning and natural language processing to analyze text, selects a taxonomy associated with the privacy policy top-level category and determines whether portions of the text corresponds to categories such as collecting personally-identifiable information, collecting non-personally-identifiable information, sharing collected information, and allowing opt-out (e.g. semantically analyzing privacy policy text to determine a plurality of privacy policy elements.). ]
Levi further teaches that classifiers recognize categories and associated vales and that advisory system 400 may issue a list of values for each category and subcategory [e.g. Levi; Abstract, Para. 0031-0034 – training text includes values associated with categories and subcategories, the classifier is trained to recognize categories and associated values and the advisory system may issue a list of values for each category and subcategory].
While Levi teaches the privacy policy analysis system of claim 1 and teaches the privacy policy analysis, identification of element of the privacy policy and associated values, Levi does not explicitly teach determining an element score for one or more of the plurality of privacy policy elements and generating the overall privacy policy score from the element score.
However, Zahran teaches a quantitative scoring technique using semantic classifier 206 matching content in an unstructured data item to pre-identified semantic information and calibration processor 214 assigning weighted numerical values to individual pieces of pre-identified content. [e.g. Zahran; Para. 0041-0043 – Zahran discloses semantic classifier 206 uses machine learning algorithms to identify relevant content and calibration processor 214 determines a threat score for each piece of content, the threat scores being weighted numerical values (e.g. determining an element score for identified semantic content.)]
Zahran further combining those individual scores to produce a total score. [e.g. Zahran; Para. 0048 – Zahran discloses content scorer 212 references threat scores for matching pre-identified information and “adds each of the threat score to determining a total semantic threat score” (e.g. generating an overall score from the element score). Additionally see Para. 0080-0083 that discloses matching phrases having corresponding scores and the section scores are combined to generate a total score.]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply Zahran’s quantitative semantic scoring technique to the privacy policy information extracted by Levi with the advantage of providing moderation on unstructured information where “there is no defined data format that identifies the importance of the information” as disclosed by Zahran paragraphs 0003-0004.
The combined system would result in Levi’s natural language processor and classifier system identifying the privacy policy categories and corresponding policy information and Zahran quantitative scoring technique would assigned respective numerical values or scores to the identified information and these element scores would be combined to determine the overall privacy policy score.
Levi as modified by Zahran further teaches outputting the privacy policy score. [e.g. Levi; Para. 0035, 0043 – Levi discloses extracted policy 442 is output, displayed on display 422 or transmitted through communication interface 426 to user computer 430 (e.g. outputting the resulting privacy policy assessment. Levi further discloses a score card may be presented to the user as well. Zahran score would be attached to the assessment.]
Regarding claim 8 and 15 they are method and manufacture claims essentially corresponding to the above recitations, and they are rejected, at least, for the same reasons.
Claim 6
Levi in view of Zahran teaches the privacy policy analysis system of claim 1, wherein: determining the element score for the one or more of the plurality of privacy policy elements comprises comparing at least one of the plurality of privacy policy elements to pre-scored text to automatically generate the element score for the at least one of the plurality of privacy policy elements. [e.g. Zahran; Para. 0041-0043, 0048 – Zahran discloses semantic classifier 206 compares content in the data item to pre-identified semantic information (e.g. comparing identified policy text to pre-identified text), the pred-identified information has associated weighted numerical scores (e.g. pre-scored text) and content scorer 212 references the scores associated with matching information to determine the resulting semantic score (e.g. automatically generating an element score.)]
Claim 9
Levi in view of Zahran teaches the method of analyzing a privacy policy of claim 8, wherein: determining the element score for one or more of the plurality of privacy policy elements and generating the privacy policy score is done using a machine learning model. [e.g. Levi; Claims 4-7, Para. 0004-0007, 0013, 0018 – Levi discloses classifiers use machine learning and natural language processing techniques. Zahran; Para. 0041-0043, 0048 – Zahran discloses semantic classifier 206 using one or more machine learning algorithms to identify the content used in scoring with content scorer 212 determining the resulting scores from the classifications (e.g. use of a machine learning model in determining the element and resulting aggregate score.).]
Claim 11
Levi in view of Zahran teaches the method of analyzing a privacy policy of claim 8, wherein: determining the element score for one or more of the plurality of privacy policy elements comprises analyzing language used in each of the plurality of privacy policy elements separately to determine the element score for each element of the plurality of privacy policy elements; and generating the privacy policy score comprises one or both of combining and interpolating the element scores to determine the privacy policy score. [e.g. Levi; Para. 0034 – Levi discloses one classifier may be associated with one or more categories and alternatively “for each category a dedicated classifier may be associated therewith” and for each subcategory a dedicated classifier may likewise be associated therewith (e.g. separately analyzing language corresponding to respective privacy policy elements). Zahran; Para. 0043, 0048, 0080-0083 – Zahran discloses matching semantic content receives corresponding scores and content scorer 212 adds the individual scores or combines section scores to determine a total score (e.g. combining element scores to determine the privacy policy score.).]
Claim 20
Levi teaches the non-transitory computer-readable medium of claim 15, wherein: the plurality of privacy policy elements comprise at least one of a type of data collected, a method used to collect the data, a use for the data, or language used to define a data collection or data usage opt-out policy. [e.g. Levi; Claim 9, Para. 0019, 0028-0030 – Levi discloses privacy policy elements including collecting personally-identifiable information, collecting non-personally-identifiable information, sharing collected information, and allowing opt-out. (e.g. at least a type of data collected and language defining a data collection/data usage opt-out policy). ]
Claims 2, 3 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over US 20130297626 A1 to Levi et al. (hereinafter “Levi”) in view of US 20140283055 A1 to Zahran et al. (hereinafter “Zahran”) and further in view of US 20060253583 A1 to Dixon et al. (hereinafter “Dixon”)
Claim 2
While Levi and Zahran teaches the privacy policy analysis system of claim 1 the combination does not explicitly teach receiving the privacy policy comprises receiving a website address from a user device; and the instructions further cause the one or more processors to: search a privacy policy database for the website address; and when the website address is present in the privacy policy database, retrieve the privacy policy score from the privacy policy database.
However, Dixon teaches receiving the privacy policy comprises receiving a website address from a user device; and the instructions further cause the one or more processors to: search a privacy policy database for the website address; and when the website address is present in the privacy policy database, retrieve the privacy policy score from the privacy policy database. [e.g. Dixon; Para. 0126, 0141-0143 – Dixon discloses a user enters or attempts to access a URL (e.g. receiving a website address from a user device), the reputation service identifies the URL and uses a real time database query interface to query the reputation of Web content associated with that URL (e.g. searching a database for the website address) and server 110 accesses reputation information previously stored in the database for the URL (e.g. retrieving a previously determined score when the website address is present)]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention store and retrieve the combined Levi and Zahran privacy policy scores using Dixon’s URL-based reputation database the advantage of “caching of the results of this real time database locally on client computers to improve performance” as disclosed by Dixon paragraphs 0008.
Claim 3
While Levi and Zahran teaches the privacy policy analysis system of claim 1 the combination does not explicitly teach receiving the privacy policy comprises receiving a website address from a user device; and the instructions further cause the one or more processors to: search a privacy policy database for the website address; and when the website address is present in the privacy policy database, retrieve the privacy policy score from the privacy policy database.
However, Dixon teaches receiving the privacy policy comprises receiving a website address from a user device; and the instructions further cause the one or more processors to: search a privacy policy database for the website address; and when the website address is present in the privacy policy database, retrieve the privacy policy score from the privacy policy database. [e.g. Dixon; Para. 0126, 0141-0143 – Dixon discloses a user enters or attempts to access a URL (e.g. receiving a website address from a user device), the reputation service identifies the URL and uses a real time database query interface to query the reputation of Web content associated with that URL (e.g. searching a database for the website address) and server 110 accesses reputation information previously stored in the database for the URL (e.g. retrieving a previously determined score when the website address is present)]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention store and retrieve the combined Levi and Zahran privacy policy scores using Dixon’s URL-based reputation database the advantage of “caching of the results of this real time database locally on client computers to improve performance” as disclosed by Dixon paragraphs 0008.
Claim 10
While Levi and Zahran teaches the method of analyzing a privacy policy of claim 8 and discloses outputting the resulting privacy policy score the combination does not explicitly teach publishing that score to a Web page.
However, Dixon teaches presenting website reputation information directly to a Web page. [e.g. Dixon; Para. 0292, 0293 – Dixon discloses a Website reputation graphical user interface displays reputation information and in certain cases “the system may show information as an in-page message in the actual HTML page” with the in-page message indicating the site’s reputation regarding use of personal information (e.g. publishing a website assessment to a Web page.)]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to publish the combined Levi and Zahran privacy policy score using Dixon’s in-page reputation presentation with the benefit of making website reputation information available so that “so that users can make informed decisions about whether to use those websites” as disclosed by Dixon paragraphs 0228.
Claims 4 and 5 are rejected under 35 U.S.C. 103 as being unpatentable over US 20130297626 A1 to Levi et al. (hereinafter “Levi”) in view of US 20140283055 A1 to Zahran et al. (hereinafter “Zahran”) and further in view of US 20090132524 A1 to Stouffer et al. (hereinafter “Stouffer”)
Claim 4
While Levi and Zahran teaches the privacy policy analysis system of claim 1, including generating the privacy policy score, the combination does not explicitly teach receiving the privacy policy comprises receiving a URL of the privacy policy from a privacy policy score web page visited by a user device
However, Stouffers teaches receiving the privacy policy URL through a web page visited by a user. [e.g. Stouffers; Para. 0045, 0047, 0050 – Stouffers discloses a user enters a URL for a website or network document to be analyzed and a webpage scoresheet 603 is displayed (e.g. receiving a URL of a document through a score web page.) Stouffers further discloses a dashboard interface 700 is presented to a user over a network for display at the user’s location and includes search bar 703 for entering the URL of the website to be analyzed (e.g. score web page visited by a user device from which the URL is received)]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to provide the Levi and Zahran privacy policy scoring system through Stouffer’s URL based scoring interface with the advantage of providing a “transparent and navigable interface” through which a user may view and understand how a network document is scored as disclosed by Stouffers paragraphs 0005.
Claim 5
Levi in view of Zahran and Stouffers teaches the privacy policy analysis system of claim 4, wherein outputting the privacy policy score comprises providing the privacy policy score to the user device. [e.g. Stouffers; Para. 0070, 0071, 0098 – Stouffers discloses scoresheet 1100 provides webpage score 1115, which provides an overall score for the page (e.g. providing the score to the user device). Stouffers further discloses the optimization engine returns a score and analysis of the website and displays the requested analysis to the user]
Claims 7, 13, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over US 20130297626 A1 to Levi et al. (hereinafter “Levi”) in view of US 20140283055 A1 to Zahran et al. (hereinafter “Zahran”) and further in view of US 20050257250 A1 to Mitchell et al. (hereinafter “Mitchell”)
Claim 7
While Levi and Zahran teaches the privacy policy analysis system of claim 1, including quantitative scoring of identified policy information such as assigning individual numerical scores to the identified semantic content before combining the scores into a final total score, the combination does not explicitly teach applying a predetermined privacy rule set to identify policy statements having weak privacy characteristics and assigning a preliminary score that contributes to the privacy policy score.
However, Mitchell teaches applying a predetermined privacy rule set to identify policy statements having weak privacy characteristics and assigning a preliminary score that contributes to the privacy policy score. [e.g. Mitchell; Para. 0048-0050, 0055. 0056, 0065-0071, 0091-0094 – Mitchell discloses logical privacy rules operate on tokens contained in the compact privacy policy and return decisions such as accept, prompt reject, leash or downgrade (e.g. processing privacy policy information against a set of predetermined rules.) Mitches further teaches privacy settings under which certain policy configurations are classified as “Unsatisfactory” including where policy purposes, recipients or opt-out attributes fail the configurated privacy criteria (e.g. identifying policy information having weak privacy characteristics under a broad and reasonable interpretation). Lastly Mitchell teaches each valid token is evaluated under the user preference rules and applicable rules are evaluated against the compact policy.]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply Mitchell’s rule based privacy evaluation to the privacy policy elements identified by Levi and scored by Zahran with the advantage of providing users “more-refined control” over privacy treatment as disclosed by Mitchell paragraphs 0046.
Claim 13
While Levi and Zahran teaches the method of analyzing a privacy policy of claim 8, and Levi further teaches receiving text through an input device such as a keyboard [Levi; Para. 0033, 0034 (e.g. receiving the privacy policy text from a user], the combination does not explicitly teach determining whether user preferences associated with the user exists, retrieving the user preferences and customizing the privacy policy score according to the retrieved preferences.
However, Mitchell teaches applying a predetermined privacy rule set to identify policy statements having weak privacy characteristics and assigning a preliminary score that contributes to the privacy policy score. [e.g. Mitchell; Para. 0087-0089, 0092-0094 – Mitchell discloses a per-site store is checked to determine whether a previous decision exists, user preferences are read from user preference database 310 and the system determines whether an applicable constant preference is stored (e.g. determining whether user preferences exist and retrieving the user preferences.) Mitchell further teaches for each valid compact policy token, the user preference rules are consulted, the result is updated according to the applicable user setting and the applicable preference rule result is returned as the final result (e.g. customizing the privacy evaluation based on the retrieved preferences.)]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply Mitchell’s rule based privacy evaluation to the privacy policy elements identified by Levi and scored by Zahran with the advantage of providing users “more-refined control” over privacy treatment as disclosed by Mitchell paragraphs 0046.
Thus the resulting combination Zahran privacy policy score would be modified according to Mitchell’s retrieved user preferences and Levi’s existing output mechanism would output the resulting customized score [e.g. Levi; para. 0035].
Claim 14
While Levi and Zahran teaches the method of analyzing a privacy policy of claim 8, and Levi further teaches receiving text through an input device such as a keyboard [Levi; Para. 0033, 0034 (e.g. receiving the privacy policy text from a user], the combination does not explicitly teach determining whether user preferences associated with the user exists, retrieving the user preferences and customizing the privacy policy score according to the retrieved preferences.
However, Mitchell teaches applying a predetermined privacy rule set to identify policy statements having weak privacy characteristics and assigning a preliminary score that contributes to the privacy policy score. [e.g. Mitchell; Para. 0087-0089, 0092-0094 – Mitchell discloses a per-site store is checked to determine whether a previous decision exists, user preferences are read from user preference database 310 and the system determines whether an applicable constant preference is stored (e.g. determining whether user preferences exist and retrieving the user preferences.) Mitchell further teaches for each valid compact policy token, the user preference rules are consulted, the result is updated according to the applicable user setting and the applicable preference rule result is returned as the final result (e.g. customizing the privacy evaluation based on the retrieved preferences.)]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply Mitchell’s rule based privacy evaluation to the privacy policy elements identified by Levi and scored by Zahran with the advantage of providing users “more-refined control” over privacy treatment as disclosed by Mitchell paragraphs 0046.
Thus the resulting combination Zahran privacy policy score would be modified according to Mitchell’s retrieved user preferences and Levi’s existing output mechanism would output the resulting customized score [e.g. Levi; para. 0035].
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over US 20130297626 A1 to Levi et al. (hereinafter “Levi”) in view of US 20140283055 A1 to Zahran et al. (hereinafter “Zahran”) and further in view of US 20070100817 A1 to Acharya et al. (hereinafter “Acharya”)
Claim 12
While Levi and Zahran teaches the method of analyzing a privacy policy of claim 8, including analyzing privacy policy text and generating a privacy policy score, the combination does not explicitly teach detecting a subsequent change in the policy text and determining an adjusted score based on the changes.
However, Acharya teaches detecting a subsequent change in the policy text and determining an adjusted score based on the changes..[e.g. Acharya; Para. 0023, 0049-0052, 0054 – Acharya discloses that a document includes a web site or web page containing textual information (e.g. web based textual document), determining how document content changes over time and may monitor a term vector, important portions, a summary, similarity hash or the full document for changes (e.g. detecting and processing changed text or content) and altering a score associated with the document based, at least in part, on information relating to a manner in which the document's content changes over time (e.g. determining an adjusted scored based on changed text).]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply Acharya’s document change monitoring and score adjustment technique to the privacy policy documents analyzed by the combination of Levi and Zahran with the benefit of addressing “stale” documents that “degrade the search results” as disclosed by Acharya paragraphs 0008.
Claims 16-19 are rejected under 35 U.S.C. 103 as being unpatentable over US 20130297626 A1 to Levi et al. (hereinafter “Levi”) in view of US 20140283055 A1 to Zahran et al. (hereinafter “Zahran”) and further in view of US 20050240580 A1 to Zamir et al. (hereinafter “Zamir”)
Claim 16
While Levi and Zahran teaches the non-transitory computer-readable medium of claim 15, including quantitative scoring of identified policy information such as assigning individual numerical scores to the identified semantic content and the privacy policy elements represents categories such as collection of personally-identifiable information, sharing collected information and opt-out, the combination does not explicitly teach the privacy policy score is generated based at least in part on user preferences associated with one or more of the plurality of privacy policy elements.
However, Zamir teaches associating user preferences with respective categories and using the category based preference information in determining a resulting score.[e.g. Zamir; Para. 0041-0045, 0077-0080 – Zamir discloses a category based profile represents user preferences with respect to respective categories, wherein each category has an associated weight indicating the extent of correlation between the category and the user’s preferences (e.g. user preferences associated with respective categories). Zamir further discloses category based profile information is used in determining the personalized score (e.g. generating a score at least partly on the user preferences.).]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to apply Zamir’s category based user preferences to the privacy policy elements identified by Levi when generating the combined Levi Zahran privacy policy score with the advantage of avoiding a generic score that “may not appropriately reflect [the] importance to a particular user” as disclosed by Zamir paragraphs 0080.
Claim 17
Levi in view of Zahran and Zamir teaches the non-transitory computer-readable medium of claim 16, wherein: the user preferences are associated with a single user.[e.g. Zamir; Para. 0032, 0040-0045– Zamir discloses user profile 230 characterizes user interest or preferences of an individual user, including term-based and category based preferences (e.g. user preferences associated with a single user.).]
Claim 18
While Levi and Zahran teaches the non-transitory computer-readable medium of claim 16, including quantitative scoring of identified policy information such as assigning individual numerical scores to the identified semantic content and the privacy policy elements represents categories such as collection of personally-identifiable information, sharing collected information and opt-out, the combination does not explicitly teach the user preferences are obtained from survey responses from a plurality of users.
However, Zamir teaches obtaining preferences from survey responses and aggregating preference information from multiple users.[e.g. Zamir; Para. 0032, 0046, 0085 – Zamir discloses a user profile may be created by requiring a user to fill in a form or answer a survey (e.g. obtaining user preferences from survey responses). Zamir further discloses an aggregate profile may be based on information associated with multiple users and profiles of a group of users may be combined into a group profile representing the preferences of the various group member (e.g. preferences obtained from a plurality of users.).]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to use Zamir’s survey based preference acquisition for the plurality of users who preferences are aggregated in order to form a group profile representing a “combination or mixture of the search preferences of the various “users as disclosed by Zamir paragraphs 0085.
Claim 19
While Levi and Zahran teaches the non-transitory computer-readable medium of claim 16, including quantitative scoring of identified policy information such as assigning individual numerical scores to the identified semantic content and the privacy policy elements represents categories such as collection of personally-identifiable information, sharing collected information and opt-out, the combination does not explicitly teach using a weighting factor for various aspects based on the preferences, with each weighing factor used to generate the score.
However, Zamir teaches assigning respective weights to categories based on user preferences.[e.g. Zamir; Para. 0041-0045, 0078, 0080 – Zamir terms and categories representing user preferences are assigned respective weights indicating importance or correlation with the user’s preferences (e.g. producing weighting factors for respective aspects based on the preferences). Zamir further discloses combining the respective weights in determining a resulting personalized score (e.g. each weighting factor being used to generate the resulting score.).]
Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to use Zamir’s preference derived category weights when generating the Levi Zahran privacy policy score with the advantage that the relevance of information to the user can be accurately characterized using profile ranks as disclosed by Zamir paragraphs 0080.
Conclusion
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/CHRISTOPHER C HARRIS/Primary Examiner, Art Unit 2432
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