DETAILED ACTION
Claims 1-20 have been examined and are pending.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 an abstract idea without significantly more. The claim(s) recite(s) monitoring user behavior to determine application permissions which is organizing human behavior. This judicial exception is not integrated into a practical application because the recited computer elements do not add a meaningful limitation to the abstract idea because they amount to implementing the abstract idea on a computer. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they are well-understood, routine, conventional computer functions.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over US Pub. No. 2023/0315277 to Sun et al. (hereinafter “Sun”) and further in view of US Pub. No. 2022/0237540 to Park et al. (hereinafter “Park”).
As to Claim 1, Sun discloses a method for controlling framework units for accessing content on an electronic device, the method comprising:
capturing an interaction indicative of an interaction of a user with respect to each content type of the content (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period);
extracting a set of attribute values based on the content and the optimal interaction, wherein the set of attribute values is indicative of user behaviour patterns with respect to each content type (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period);
[classifying] the content based on the extracted set of attributes values, wherein the classification determines a sensitivity of the content as either of interest or not of interest (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat); and
controlling access to the content for one or more applications associated with the electronic device based on the classified content being one of interest or not of interest to the user (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
Sun does not explicitly disclose classifying the content.
However, Park discloses this. Paragraph [0021] of Park discloses classifying an exam associated with particular user interactions allows the model to more accurately identify inefficient user interaction patterns.
It would have been obvious to one of ordinary skill in the art before the effective filing of the invention to combine the user behavior system as disclosed by Sun, with classifying content as disclosed by Park. One of ordinary skill in the art would have been motivated to combine to apply a known technique to a known device ready for improvement to yield predictable results. Sun and Park are directed toward user behavior systems and as such it would be obvious to use the techniques of one in the other. Paragraph [0021] of Park discloses this allows the model to more accurately identify user interactions patterns.
As to Claim 2, Sun-Park discloses the method as claimed in claim 1, wherein capturing the interaction comprises:
receiving, from a set of framework units associated with the electronic device, a stream of interactions associated with the electronic device (Paragraph [0233] of Sun discloses the terminal device may count the number of times the user has posted on WeChat Moments in a recent time period (such as a week or a month), and the number of times the user selects “Show location” when posting on WeChat Moments);
generating composite interactions based on the received stream of interactions and the content (Paragraph [0233] of Sun discloses the terminal device may count the number of times the user has posted on WeChat Moments in a recent time period (such as a week or a month), and the number of times the user selects “Show location” when posting on WeChat Moments);
analysing the composite interactions based on an interaction classifier model (Paragraph [0234] of Sun discloses the terminal device may provide scores for the number of times the user posts on WeChat Moments and the number of times the user selects “Show location” when posting on WeChat Moments as dimensions, respectively); and
selecting the interaction based on the analysis of the composite interactions (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
As to Claim 3, Sun-Park discloses the method as claimed in claim 1, wherein extracting the set of attribute values comprises:
filtering the content and the interaction to generate filtered data, wherein filtering the content and the interaction comprises removal of outliers, anomalies, and corrupted data; converting the filtered data to a specified format; and extracting the set of attribute values from the filtered data in the specified format based on one or more pattern recognition techniques (Paragraph [0022] of Park discloses preprocessing or filtering may be performed on the set of examples, such as to eliminate “noise” (for example, outlier sequences, incomplete sequences, sequences expanding more than a predetermined amount of time, or the like). Paragraph [0021] of Park discloses classifying an exam associated with particular user interactions allows the model to more accurately identify inefficient user interaction patterns.).
Examiner recites the same rationale to combine used for claim 1.
As to Claim 4, Sun-Park discloses the method as claimed in claim 1, wherein classifying the content comprises:
determining a data type associated with set of attribute values (Paragraph [0231] of Sun discloses the terminal device may further automatically set the privacy precision for the application in a personalized manner for different users, different applications, different time or time periods, and other dimensions, without needing the user’s operation, improving user experience);
selecting an estimation model from among a plurality of estimation models based on the determined data type (Paragraph [0231] of Sun discloses the terminal device may further automatically set the privacy precision for the application in a personalized manner for different users, different applications, different time or time periods, and other dimensions, without needing the user’s operation, improving user experience);
determining, based on the selected estimation model, a first probability value associated with sensitivity of the content being of interest and a second probability value associated with sensitivity of the content being not of interest (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat); and
classifying the content based on the first probability value and the second probability value (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
As to Claim 5, Sun-Park discloses the method as claimed in claim 4, wherein at least one estimation model of the plurality of estimation models comprises a trained mathematical model stored on the electronic device, and wherein the at least one estimation model is configured to be trained based on a global estimation model stored on a cloud-based server (Paragraph [0234] of Sun discloses the terminal device may provide scores for the number of times the user posts on WeChat Moments and the number of times the user selects “Show location” when posting on WeChat Moments as dimensions, respectively. For each dimension, the scoring result is related to the corresponding number of times. A larger number of times indicates a higher score, and a smaller number of times indicates a lower score. The terminal device may calculate a sum or a weighted sum of scores of the two dimensions as the user’s behavior score for WeChat, and set the location information precision for WeChat based on the behavior score. A higher behavior score corresponds to a higher location information precision, and a lower behavior score corresponds to a lower location information precision. Paragraph [0239] of Sun discloses The privacy configuration list may be pre-written into the operating system of the terminal device, or may be obtained from a specified server after the terminal device is activated, or may be imported by the user, which is not limited in this embodiment of this disclosure).
As to Claim 6, Sun-Park discloses the method as claimed in claim 1, wherein controlling access to the content comprises: determining, based on the content and the interaction, a plurality of possible tracking methods utilized by the one or more applications to track the content; selecting one or more feasible tracking methods from among the plurality of possible tracking methods; based on the content being determined to be of interest to the user, generating access instructions indicative of blocking access to the content; and sending the generated access instructions to corresponding framework units from among a set of framework units to control the access to the content by the one or more applications (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat)
As to Claim 7, Sun-Park discloses the method as claimed in claim 1, wherein the content type is associated with one or more of pictures, music, video, text, link, audio, document, and visual action elements (Paragraph [0234] of Sun discloses the terminal device may provide scores for the number of times the user posts on WeChat Moments and the number of times the user selects “Show location” when posting on WeChat Moments as dimensions, respectively.).
As to Claim 8, Sun-Park discloses the method as claimed in claim 1, wherein the interaction is associated with one or more of touch, physical buttons, gestures, voice commands, text input, navigation, application interactions, media controls, camera and multimedia, communication, notifications, security, settings, customization, file management, payments, accessibility, smart device control, gaming, screen recording, search, battery, power management, and emergency services (Paragraph [0234] of Sun discloses the terminal device may provide scores for the number of times the user posts on WeChat Moments and the number of times the user selects “Show location” when posting on WeChat Moments as dimensions, respectively.).
As to Claim 9, Sun discloses a system for controlling framework units for accessing content on an electronic device, the system comprising: a memory configured to store a plurality of modules in the form of programmable instructions; at least one processor, comprising processing circuitry, communicatively coupled to the memory, at least one processor, individually and/or collectively, configured to execute the programmable instructions associated with the plurality of modules, the plurality of modules comprising:
an interaction estimator configured to capture an interaction indicative of an interaction of a user with respect to each content type of the content (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period);
an attribute extractor configured to extract a set of attribute values based on the content and the interaction, wherein the set of attribute values is indicative of user behaviour patterns with respect to each content type (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period);
an interest estimator configured to [classify] the content based on the extracted set of attributes values, wherein the classification determines the sensitivity of the content as either of interest or not of interest (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat); and
a privacy controller configured to control access to the content for one or more applications associated with the electronic device based on the classified content being one of interest or not of interest to the user (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
Sun does not explicitly disclose classifying the content.
However, Park discloses this. Paragraph [0021] of Park discloses classifying an exam associated with particular user interactions allows the model to more accurately identify inefficient user interaction patterns.
Examiner recites the same rationale to combine used for claim 1.
As to Claim 10, Sun-Park discloses the system as claimed in claim 9, wherein to capture the optimal interaction, the interaction estimator is configured to: receive, from a set of framework units associated with the electronic device, a stream of interactions associated with the electronic device (Paragraph [0233] of Sun discloses the terminal device may count the number of times the user has posted on WeChat Moments in a recent time period (such as a week or a month), and the number of times the user selects “Show location” when posting on WeChat Moments);
generate composite interactions based on the received stream of interactions and the content (Paragraph [0233] of Sun discloses the terminal device may count the number of times the user has posted on WeChat Moments in a recent time period (such as a week or a month), and the number of times the user selects “Show location” when posting on WeChat Moments);
analyse the composite interactions based on an interaction classifier model (Paragraph [0234] of Sun discloses the terminal device may provide scores for the number of times the user posts on WeChat Moments and the number of times the user selects “Show location” when posting on WeChat Moments as dimensions, respectively); and
select the interaction based on the analysis of the composite interactions (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat)
As to Claim 11, Sun-Park discloses the system as claimed in claim 9, wherein to extract the set of attribute values, the attribute extractor is configured to: filter the content and the interaction to generate filtered data, wherein filtering the content and the interaction comprises removal of outliers, anomalies, and corrupted data; convert the filtered data to a specified format; and extract the set of attribute values from the filtered data in the specified format based on one or more pattern recognition techniques (Paragraph [0022] of Park discloses preprocessing or filtering may be performed on the set of examples, such as to eliminate “noise” (for example, outlier sequences, incomplete sequences, sequences expanding more than a predetermined amount of time, or the like). Paragraph [0021] of Park discloses classifying an exam associated with particular user interactions allows the model to more accurately identify inefficient user interaction patterns.).
Examiner recites the same rationale to combine used for claim 1.
As to Claim 12, Sun-Park discloses the system as claimed in claim 9, wherein to classify the content, the interest estimator is configured to: determine a data type associated with set of attribute values (Paragraph [0231] of Sun discloses the terminal device may further automatically set the privacy precision for the application in a personalized manner for different users, different applications, different time or time periods, and other dimensions, without needing the user’s operation, improving user experience);
select an estimation model from among a plurality of estimation models based on the determined data type (Paragraph [0231] of Sun discloses the terminal device may further automatically set the privacy precision for the application in a personalized manner for different users, different applications, different time or time periods, and other dimensions, without needing the user’s operation, improving user experience);
determine, based on the selected estimation model, a first probability value associated with sensitivity of the content being of interest and a second probability value associated with sensitivity of the content being not of interest (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat); and
classify the content based on the first probability value and the second probability value (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
As to Claim 13, Sun-Park discloses the system as claimed in claim 9, wherein at least one estimation model of the plurality of estimation models comprises a trained mathematical model stored on the electronic device, and wherein the at least one estimation model is configured to be trained based on a global estimation model stored on a cloud-based server (Paragraph [0234] of Sun discloses the terminal device may provide scores for the number of times the user posts on WeChat Moments and the number of times the user selects “Show location” when posting on WeChat Moments as dimensions, respectively. For each dimension, the scoring result is related to the corresponding number of times. A larger number of times indicates a higher score, and a smaller number of times indicates a lower score. The terminal device may calculate a sum or a weighted sum of scores of the two dimensions as the user’s behavior score for WeChat, and set the location information precision for WeChat based on the behavior score. A higher behavior score corresponds to a higher location information precision, and a lower behavior score corresponds to a lower location information precision. Paragraph [0239] of Sun discloses The privacy configuration list may be pre-written into the operating system of the terminal device, or may be obtained from a specified server after the terminal device is activated, or may be imported by the user, which is not limited in this embodiment of this disclosure).
As to Claim 14, Sun-Park discloses the system as claimed in claim 9, wherein controlling access to the content is configured to: determine, based on the content and the interaction, a plurality of possible tracking methods utilized by the one or more applications to track the content; select one or more feasible tracking methods from among the plurality of possible tracking methods; based on the content being determined to be of interest to the user, generate access instructions indicative of blocking access to the content; and send the generated access instructions to corresponding framework units from among a set of framework units to control the access to the content by the one or more applications (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat)
As to Claim 15, Sun discloses a method for dynamically restricting applications from accessing content in an electronic device, the method comprising:
capturing user interactions with content types, the captured user interactions forming user behavior patterns on the attributes indicative of responses of a user to each content type (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period);
training an on-device machine learning model based on the content types and captured interactions to extract attributes specific to the user (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period);
[classifying] content based on extracted attributes, wherein the classification determines the sensitivity of the content as either of interest or not of interest (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat);
capturing user behavior when interacting with new content on the electronic device (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat);
predicting, using the trained on-device machine learning model, whether the interaction with new content resulting interest or not of interest to user in content (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat); and
controlling access to the content by the applications on the electronic device (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
Sun does not explicitly disclose classifying the content.
However, Park discloses this. Paragraph [0021] of Park discloses classifying an exam associated with particular user interactions allows the model to more accurately identify inefficient user interaction patterns.
Examiner recites the same rationale to combine used for claim 1.
As to Claim 16, Sun-Park discloses the method as claimed in claim 15, wherein the capturing is performed by a first monitoring service and a second monitoring services run by the applications and the electronic device respectively (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
As to Claim 17, Sun-Park discloses the method as claimed in claim 15, wherein based on the user interacting with the content on the applications, one of the first monitoring service running in the applications monitors users' interactions or the second monitoring service running in the electronic device monitors user interactions (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
As to Claim 18, Sun discloses a system for dynamically restricting applications from accessing content in an electronic device, the system comprising: a memory configured to store a plurality of modules in the form of programmable instructions; at least one processor, comprising processing circuitry, communicatively coupled to the memory, at least one processor, individually and/or collectively, configured to execute the programmable instructions associated with the plurality of modules, the plurality of modules comprising:
an interaction estimator configured to capture user interactions with content types, the captured user interactions forming user behavior patterns on the attributes indicative of responses of a user to each content type (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period);
an interaction estimator configured to trained an on-device machine learning model based on the content types and captured interactions to extract attributes specific to the user (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period);
an interaction estimator configured to [classify] content based on extracted attributes, wherein the classification determines the sensitivity of the content as either of interest or not of interest (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat);
an interaction estimator configured to capture user behavior when interacting with new content on the electronic device (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat);
an interaction estimator configured to predict, using the trained on-device machine learning model, whether the interaction with new content resulting interest or not of interest to user in content (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat); and
an interaction estimator configured to control access to the content by the applications on the electronic device (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
Sun does not explicitly disclose classifying the content.
However, Park discloses this. Paragraph [0021] of Park discloses classifying an exam associated with particular user interactions allows the model to more accurately identify inefficient user interaction patterns.
Examiner recites the same rationale to combine used for claim 1.
As to Claim 19, Sun-Park discloses the system as claimed in claim 18, wherein the capturing is configured to perform by a first monitoring service and a second monitoring services run by the applications and the electronic device respectively (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
As to Claim 20, Sun-Park discloses the system as claimed in claim 18, wherein based on the user interacting with the content on the applications, one of the first monitoring service running in the applications monitors users' interactions or the second monitoring service running in the electronic device monitors user interactions (Paragraph [0232] of Sun discloses determine, based on the user’s behavior of using WeChat within a historical time period, whether the user is willing to provide location information to WeChat for use. If the terminal device determines that the user is willing to provide the location information to WeChat for use, the terminal device may provide high-precision location information for WeChat. If the terminal device determines that the user is unwilling to provide the location information to WeChat for use, the terminal device provides low-precision location information for WeChat).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kevin S Mai whose telephone number is (571)270-5001. The examiner can normally be reached Monday to Friday 9AM to 5PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Philip Chea can be reached at 5712723951. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/KEVIN S MAI/Primary Examiner, Art Unit 2499