DETAILED ACTION
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 .
Response to Arguments
Applicant's arguments and amendments received June 08, 2026 have been fully considered. with regard to 35 U.S.C. § 102, Applicant argues that the cited prior art does not disclose “see applicant argument pages 9-12”. This language corresponds to claims 1-19 and 20.
As such, these have been considered but they are not persuasive as addressed below. See the rejection how the art on record reads on the claimed invention as well as the examiner's interpretation of the cited art in view of the presented claim set as outlined below. Furthermore, in response to applicant argument, the system of Modarresi at least at first step collect user activity accessing webpages and the information stored for future use or predication; at second step user activity majored or classified by identify the minimum prior event user with the highest probability as the predicted corresponding minimum prior event user; and third or following step by target user identification system, provides digital content with customized webpage. Therefore, the method of identify a second probability that the user has transitioned from the first state into a second state during a time period anticipated by Modarresi as outlined above and below, see following under 102 rejections.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 7-11, 17-19 and 20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Modarresi US 2019/0273789.
In regarding to claim 1 Modarresi teaches:
1. A system comprising: one or more processors; and one or more non-transitory computer-readable media storing computing instructions, that when executed on the one or more processors, cause the one or more processors to: automatically customize, based on a first state of a user, first content for a graphical user interface on an electronic device of the user;
[0055] As mentioned, the target user identification system 108 may provide digital content to one or more of the client devices 114. Indeed, the target user identification system 108 can distribute (e.g., via the network 102) digital content to users 118 by way of the client devices 114. For example, the target user identification system 108 can generate and/or provide digital content customized for specific users based on information within the user information database 112.
[0060] Furthermore, the target user identification system 108 can detect additional events associated with the user 118a. In particular, the target user identification system 108 can detect the user 118a visiting a webpage, opening another application, accessing a website, clicking a link within a web site, purchasing a product via a web site, or some other type of event. As mentioned, the target user identification system 108 can determine features associated with each event detected for one or more client devices of a given user (e.g., user 118a). Accordingly, the target user identification system 108 can gather events, each event including its own event features, corresponding to the user 118a.
[0117] To elaborate, the target user identification system 108 can provide digital content by customizing an interface of a particular application (e.g., a SAAS application) with features, tools, and other attributes that the target user has previously set up for the given application. In other embodiments, the target user identification system 108 can provide digital content by prioritizing search results in a search engine interface according to previous interests of the target user (e.g., by placing links that the target user is more likely to select higher up in the results). In still other embodiments, the target user identification system 108 can provide digital content by customizing a social networking feed with content associated with other users who are linked with the target user. The target user identification system 108 can still further provide digital content by accessing files that the target user has saved during previous sessions of user activity and either transferring the files or otherwise making the files available for download to the client device associated with the target user.
Modarresi, 0055, 0060-0066, 0117-0119, emphasis added.
identify a second probability that the user has transitioned from the first state into a second state during a time period;
[0117] To elaborate, the target user identification system 108 can provide digital content by customizing an interface of a particular application (e.g., a SAAS application) with features, tools, and other attributes that the target user has previously set up for the given application. In other embodiments, the target user identification system 108 can provide digital content by prioritizing search results in a search engine interface according to previous interests of the target user (e.g., by placing links that the target user is more likely to select higher up in the results). In still other embodiments, the target user identification system 108 can provide digital content by customizing a social networking feed with content associated with other users who are linked with the target user. The target user identification system 108 can still further provide digital content by accessing files that the target user has saved during previous sessions of user activity and either transferring the files or otherwise making the files available for download to the client device associated with the target user.
Modarresi, 0117-0119, emphasis added.
determining that second probability is above a second probability predefined threshold;
[0110] Based on these probability determinations, the user classification model 110 outputs a predicted corresponding minimum prior event user 504. For instance, the target user identification system 108 can utilize the user classification model 110 to identify the minimum prior event user with the highest probability as the predicted corresponding minimum prior event user 504. To illustrate, the target user identification system 108 can compare the probability corresponding to the first minimum prior event user (e.g., 10%), the probability corresponding to the second prior event user (e.g., 50%), and the probability corresponding to the third minimum prior event user (e.g., 20%) and select the minimum prior event user with the highest probability (i.e., the second minimum prior event user) as the predicted corresponding minimum prior event user 504.
Modarresi, 0109-0110, emphasis added.
and after determining that the second probability is above the second probability predefined threshold, automatically customize, based on the second state of the user, second content for the graphical user interface on the electronic device of the user.
[0118] As mentioned, the target user identification system 108 can provide digital content to a client device associated with a target user. Indeed, FIG. 6 illustrates an example client device 114a associated with a target user. As shown in FIG. 6, the target user identification system 108 provides digital content to a smartphone. In particular, the target user identification system 108 provides digital content for a customized webpage for the target user. To illustrate, the target user identification system 108 provides digital content including a welcome message (“Welcome back, Bob!”) including the name (or other identifier) of the target user (“Bob”), a link to a news article of interest to the target user, daily stock performance of stocks associated with the target user, access to files that the target user has previously saved, and a link to purchase a product (e.g., glasses) of interest to the target user.
Modarresi, 0117-0119, emphasis added.
In regarding to claim 7 Modarresi teaches:
7. The system of claim 1, wherein, to automatically customize the first content for the graphical user interface, the computing instructions cause the one or more processors to: automatically change one or more images on the graphical user interface to first images related to the first state.
Modarresi, 0117-0119 and Fig. 6.
In regarding to claim 8 Modarresi teaches:
8. The system of claim 1, wherein, to automatically customize the first content for the graphical user interface, the computing instructions cause the one or more processors to: automatically change text displayed on the graphical user interface to first text related to the first state.
Modarresi, 0117-0119 and Fig. 6.
In regarding to claim 9 Modarresi teaches:
9. The system of claim 1, wherein, to automatically customize the first content for the graphical user interface, the computing instructions cause the one or more processors to: automatically alter a layout of the graphical user interface for the first state.
Modarresi, 0117-0119 and Fig. 6.
In regarding to claim 10 Modarresi teaches:
10. The system of claim 1, wherein the first and second state comprise life events in a sequence of life events of the user.
Modarresi, 0117-0119 and Fig. 6.
Claims 11, 17-19 and 20 list all similar elements of claims 1, 7-9 and 10, but in method form rather than system form. Therefore, the supporting rationale of the rejection to claims 1, 7-9 and 10 applies equally as well to claims 11, 17-19 and 20.
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.
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.
Claims 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Modarresi US 2019/0273789 as applied to claim 1 above, and further in view of Hoffmeister US 9, 159, 319.
In regarding to claim 2 Modarresi teaches:
2. The system of claim 1, wherein, to identify the second probability, the computing instructions cause the one or more processors to: monitor activities of the user over the time period:
[0117] To elaborate, the target user identification system 108 can provide digital content by customizing an interface of a particular application (e.g., a SAAS application) with features, tools, and other attributes that the target user has previously set up for the given application. In other embodiments, the target user identification system 108 can provide digital content by prioritizing search results in a search engine interface according to previous interests of the target user (e.g., by placing links that the target user is more likely to select higher up in the results). In still other embodiments, the target user identification system 108 can provide digital content by customizing a social networking feed with content associated with other users who are linked with the target user. The target user identification system 108 can still further provide digital content by accessing files that the target user has saved during previous sessions of user activity and either transferring the files or otherwise making the files available for download to the client device associated with the target user.
Modarresi, 0117-0119, emphasis added.
However, Modarresi fails to explicitly teach, but Hoffmeister teaches: by using a mixed model comprising a mix of a Gaussian model and a second Markov model,
(43) Hidden Markov Model States
(44) FIG. 3 illustrates an example sequence 300 of hidden Markov model (HMM) states that may be included in a word model, such as a keyword model, a background model, and/or a competitor model. As illustrated in FIG. 3, the sequence 300 includes six HMM states: S.sub.1 through S.sub.6. While six HMM states are illustrated in FIG. 3, a word model may include any number of HMM states. As discussed above, each HMM state S.sub.1 through S.sub.6 may be represented by Gaussian mixture models (GMMs) that model distributions of feature vectors.
Hoffmeister, col. 8 line 60 to col. 9 line 7, emphasis added.
Accordingly, it would have been obvious to one ordinary skill in the art before the effective filing date to combine the teaching of Hoffmeister with the system of Modarresi in order using a mixed model comprising a mix of a Gaussian model and a second Markov model, as such, the use of one or more competitor models may improve keyword spotting by creating additional points of comparison and the system reduce the number of times that a word is falsely identified as a keyword..—Col. 3 lines 41-49.
Furthermore, Modarresi teaches: and identify the second probability based on the activities of the user over the time period, wherein the second state is related to the first state.
[0117] To elaborate, the target user identification system 108 can provide digital content by customizing an interface of a particular application (e.g., a SAAS application) with features, tools, and other attributes that the target user has previously set up for the given application. In other embodiments, the target user identification system 108 can provide digital content by prioritizing search results in a search engine interface according to previous interests of the target user (e.g., by placing links that the target user is more likely to select higher up in the results). In still other embodiments, the target user identification system 108 can provide digital content by customizing a social networking feed with content associated with other users who are linked with the target user. The target user identification system 108 can still further provide digital content by accessing files that the target user has saved during previous sessions of user activity and either transferring the files or otherwise making the files available for download to the client device associated with the target user.
Modarresi, 0117-0119, emphasis added.
Claim 12 list all similar elements of claim 2, but in method form rather than system form. Therefore, the supporting rationale of the rejection to claim 2 applies equally as well to claims 12.
Note: The motivation that was applied to claim 2 above, applies equally as well to claim 12 as presented blow.
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.
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.
Claims 3-6 and 13-16 are rejected under 35 U.S.C. 103 as being unpatentable over Modarresi US 2019/0273789 as applied to claim 1 above, and further in view of Hoffmeister Gilman et al. US 2018/0253682.
In regarding to claim 3 Modarresi teaches:
3. The system of claim 1, wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to: monitor first activities of the user over a first time period;
[0117] To elaborate, the target user identification system 108 can provide digital content by customizing an interface of a particular application (e.g., a SAAS application) with features, tools, and other attributes that the target user has previously set up for the given application. In other embodiments, the target user identification system 108 can provide digital content by prioritizing search results in a search engine interface according to previous interests of the target user (e.g., by placing links that the target user is more likely to select higher up in the results). In still other embodiments, the target user identification system 108 can provide digital content by customizing a social networking feed with content associated with other users who are linked with the target user. The target user identification system 108 can still further provide digital content by accessing files that the target user has saved during previous sessions of user activity and either transferring the files or otherwise making the files available for download to the client device associated with the target user.
Modarresi, 0117-0119, emphasis added.
However, Modarresi fails to explicitly teach, but Gilman teaches: identify, using a first Markov model, a first probability of the user being in the first state; and
[0060] The customer analytics system 158 may be configured to track and analyze user behavior and attributes. In some implementations, the customer analytics system 158 records user attributes, preferences, order contents, etc., and determines additional user details based on these elements. For instance, the customer analytics system 158 may track the retail items in past orders of a user and, using past orders of other users and a computer learning algorithm (e.g., a neural network, a Hidden Markov Model, etc.), predict desires and actions of that user relative to other retail items and promotions. The system 100 is beneficial for applying these computer learning methods, because it increases user participation in trackable online interfaces and enables the customer analytics system 158 to provide relevant suggestions and promotions to the user.
Gilman, 0060, emphasis added.
Accordingly, it would have been obvious to one ordinary skill in the art before the effective filing date to combine the teaching of Gilman with the system of Modarresi in order using a mixed model comprising a mix of a Gaussian model and a second Markov model, as such, the system increases user participation in trackable online interfaces and enables the customer analytics system to provide relevant suggestions and promotions to the user..--0060.
Furthermore, Modarresi teaches: determine that the first probability is above a first probability predefined threshold.
Modarresi, 0073-0075 and 0117-0119
Note: The motivation that was applied to claim 3 above, applies equally as well to claims 4-6 and 13-16 as presented blow.
In regarding to claim 4 Modarresi and Gilman teaches:
4. The system of claim 3, furthermore, Modarresi teaches: wherein, to monitor the first activities of the user over the first time period, the computing instructions cause the one or more processors to: gather information comprising at least one of: views of an item of a category of items; cart adds of the item of the category of items; registry adds of the item of the category of items; transactions involving the item of the category of items; or searches for the item of the category of items.
Modarresi, 0117-0119
In regarding to claim 5 Modarresi and Gilman teaches:
5. The system of claim 3, furthermore, Gilman teaches: wherein the computing instructions, when executed on the one or more processors, further cause the one or more processors to: train the first Markov model to identify the first probability of the user being in the first state
Gilman, 0060
furthermore, Modarresi teaches: by at least one of: identifying one or more binary classifiers, each binary classifier of the one or more binary classifiers independently capable of identifying the first probability of the user being in the first state; or identifying a multi-class classifier capable of assigning a distribution over the first probability of the user being in the first state.
Modarresi, 0073-0075
In regarding to claim 6 Modarresi and Gilman teaches:
6. The system of claim 5, furthermore, Gilman teaches: wherein the first Markov model is trained on a deep neural network.
Gilman, 0060, 0064
Claims 13-16 list all similar elements of claims 3-6, but in method form rather than system form. Therefore, the supporting rationale of the rejection to claims 3-6 applies equally as well to claims 13-16.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL T TEKLE whose telephone number is (571)270-1117. The examiner can normally be reached Monday-Friday 8:00-4:30 ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, William Vaughn can be reached at 571-272-3922. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DANIEL T TEKLE/Primary Examiner, Art Unit 2481
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