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 .
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.
Claim 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 is directed to a process. The claim recites “translating……., the application features into entity objects”. The processes of converting/translating application features into an entity object involve observation, judgement and evaluation. Aforementioned processes can practically be performed in the human mind. Thus, the claim is directed to an abstract idea falling within the grouping of mental steps, see MPEP 2106.04(a)(2)(III).
At step 2A, prong 2, this judicial exception is not integrated into a practical application. In particular, the claim recites additional elements – “retrieving, by a computer application executed by a user electronic device for a user, a persona for the user, wherein the persona is based on user transactions and/or user inquiries to the computer application; retrieving, by the computer application, localized content for the application features”. Above mentioned step of retrieving contents recites insignificant extra-solution activity of mere data gathering is “obtaining information” as identified in MPEP 2106.05 (g).The claim further recites “providing, by the computer application, the entity objects and the localized content to an operating system for the user electronic device; wherein the operating system is configured to surface one of the application features and display the localized content in response to a user search in a search interface provided by the operating system by searching the entity objects, and to control the computer application to present the application feature”. Above mentioned steps constitutes insignificant extra-solution activity of presenting data output. The claim also mentions generic computer and generic computer components such as “electronic device”, which is recited at a high level of generality and is recited as performing generic computer functions routinely used in computer applications. Thus, which is use of a computer or generic computer components to execute abstract idea in the form of software constitutes use of the computer or its components as a tool. Accordingly, this additional elements do not integrate the abstract idea into a practical application. Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application. Therefore, claim is directed to an abstract idea.
At step 2B, the claims don’t include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements recites insignificant extra-solution activity of data gathering and outputting/transmitting data such are also well- understood, routine, and conventional. Further, sending/transmitting data is insignificant extra-solution activity of data transmission, such is also well- understood, routine, and conventional (OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)). Also, presenting data is WURC based on OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1362-63 (Fed. Cir. 2015) (presenting offers and gathering statistics). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept, see MPEP 2106.05 (f). Looking at the limitations in combination and the claim as a whole does not change this conclusion and the claim is ineligible.
Claim 8 is directed to a device or system. The claim recites “translate the application features into entity objects”. The processes of translating/converting application features into an entity object involve observation, judgement and evaluation. Aforementioned processes can practically be performed in the human mind. Thus, the claim is directed to an abstract idea falling within the grouping of mental steps, see MPEP 2106.04(a)(2)(III).
At step 2A, prong 2, this judicial exception is not integrated into a practical application. In particular, the claim recites additional elements – “retrieve, for a user, a persona for the user, wherein the persona is based on user transactions and/or user inquiries to the computer application; the computer application is configured to retrieve, via the personalization system, application features for the computer application that are relevant to the persona from the application features database; the computer application is configured to retrieve localized content for the application features from the localized content database”. Above mentioned step of retrieving persona/contents recites insignificant extra-solution activity of mere data gathering is “obtaining information” as identified in MPEP 2106.05 (g). The claim further recites “the computer application is configured to provide the entity objects and the localized content to the operating system; wherein the operating system is configured to surface one of the application features and display the localized content in response to a user search in a search interface provided by the operating system by searching the entity objects, and to control the computer application to present the application feature”. Above mentioned steps constitutes insignificant extra-solution activity of presenting data output. The claim also mentions generic computer and generic computer components such as “computer processors”, “database” and “personalization system” at a high level of generality for performing generic computer functions routinely used in computer applications; use of a computer or generic computer components to execute abstract idea in the form of software constitutes use of the computer or its components as a tool. Accordingly, this additional elements do not integrate the abstract idea into a practical application. Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application. Therefore, claim 8 is directed to an abstract idea.
At step 2B, the claims don’t include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements recites insignificant extra-solution activity of data gathering and outputting/transmitting data such are also well- understood, routine, and conventional. Further, sending/transmitting data is insignificant extra-solution activity of data transmission, such is also well- understood, routine, and conventional (OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)). Also, presenting data is WURC based on OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1362-63 (Fed. Cir. 2015) (presenting offers and gathering statistics). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept, see MPEP 2106.05 (f). Looking at the limitations in combination and the claim as a whole does not change this conclusion and the claim 8 is ineligible.
Claim 15 is directed to a product. The claim recites “translating the application features into entity objects”. The processes of translating/converting application features into an entity object involve observation, judgement and evaluation. Aforementioned processes can practically be performed in the human mind. Thus, the claim is directed to an abstract idea falling within the grouping of mental steps, see MPEP 2106.04(a)(2)(III).
At step 2A, prong 2, this judicial exception is not integrated into a practical application. In particular, the claim recites additional elements – “retrieving a persona for a user, wherein the persona is based on user transactions and/or user inquiries to a computer application; retrieving, using a personalization system, application features for the computer application that are relevant to the persona; retrieving, localized content for the application features, wherein the localized content comprises a description for each of the application features”. Above mentioned step of retrieving contents recites insignificant extra-solution activity of mere data gathering is “obtaining information” as identified in MPEP 2106.05 (g). The claim further recites “surfacing one of the application features and displaying the localized content in response to a user search in a search interface by searching the entity objects; and presenting to present the application feature”. Above mentioned steps constitutes insignificant extra-solution activity of presenting data output. The claim also mentions generic computer and generic computer components such as “computer processors” and “personalization system” at a high level of generality for performing generic computer functions routinely used in computer applications;, use of a computer or generic computer components to execute abstract idea in the form of software constitutes use of the computer or its components as a tool. Accordingly, this additional elements do not integrate the abstract idea into a practical application. Viewing the additional limitations together and the claim as a whole, nothing provides integration into a practical application. Therefore, claim 15 is directed to an abstract idea.
At step 2B, the claims don’t include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements recites insignificant extra-solution activity of data gathering and outputting/transmitting data such are also well- understood, routine, and conventional. Further, sending/transmitting data is insignificant extra-solution activity of data transmission, such is also well- understood, routine, and conventional (OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)). Also, presenting data is WURC based on OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1362-63 (Fed. Cir. 2015) (presenting offers and gathering statistics). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept, see MPEP 2106.05 (f). Looking at the limitations in combination and the claim as a whole does not change this conclusion and the claim 15 is ineligible.
Dependent claim 2-7 are directed to the same abstract idea as the independent claim from which they depend and further recite limitations – “clustering……the data points into a plurality of clusters using a clustering algorithm; identifying, ….., a persona for each of the clusters;……identifying, ……., one of the clusters for the plurality of user data points” and “the personas are based on a common feature in each of the clusters”. The process of clustering data using algorithm, identifying persona for each cluster, identifying one of the clusters for plurality of user data points and having personas based on common feature in each cluster involve observation, judgement and evaluation and can practically be performed in human mind. Accordingly, recited limitations fall into abstract idea groupings of mental process (see MPEP 2106.04(a)(2)(III)) under Step 2A, prong 1 of the 2019 PEG. Therefore, aforementioned processes can practically be performed in the human mind and directed to an abstract idea.
At step 2A, prong 2, this judicial exception is not integrated into a practical application. In particular, the claims recite additional elements – “receiving, by the backend computer program, a plurality of user data points for the user”, “the data points and the user data points comprise average monthly spends, spending categories, spending patterns, financial products owned, benefits/offers exploration/redemption rate, and/or application feature usage” and “wherein the user data points are limited to a time period”. Above mentioned step of retrieving contents recites insignificant extra-solution activity of mere data gathering is “obtaining information” as identified in MPEP 2106.05 (g). The claim further recites “the localized content comprises a description for each of the application features”. Above mentioned steps constitutes insignificant extra-solution activity of presenting data output. The claim also recited “clusters are updated periodically” which is insignificant storing data. The claim also mentions generic computer and generic computer components such as “computer processors” and “personalization system”, use of a computer or generic computer components to execute abstract idea in the form of software constitutes use of the computer or its components as a tool. Accordingly, this additional elements do not integrate the abstract idea into a practical application. Viewing the additional limitations together and the claims individually as a whole, nothing provides integration into a practical application. Therefore, claim 2-7 directed to an abstract idea.
At step 2B, the claims don’t include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above the additional elements recites insignificant extra-solution activity of data gathering and outputting/transmitting data such are also well- understood, routine, and conventional. Further, sending/transmitting data is insignificant extra-solution activity of data transmission, such is also well- understood, routine, and conventional (OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)). Also, presenting data is WURC based on OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1362-63 (Fed. Cir. 2015) (presenting offers and gathering statistics). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept, see MPEP 2106.05 (f). Looking at the limitations in combination and the claims individually as a whole does not change this conclusion and the claim is ineligible. Accordingly, claim 2-7 are not patent eligible.
Claim 8, 9, 10, 11, 12, 13 and 14 differ from claim 2, 3, 4, 5, 6 and 7 respectively in that the steps of the claimed method are implemented by instructions when executed by one or more processors. The invention of claim 8, 9, 10, 11, 12, 13 and 14 is a system including one or more processors and a memory storing the instructions to perform recited steps. For reasons discussed above, the claimed steps are directed to mental steps. Use of a processor to execute instructions stored in memory constitutes use of a generic computer as a tool and does not constitute an application of significantly more than the abstract idea. Accordingly, claim 8, 9, 10, 11, 12, 13 and 14 are not patent eligible.
Claim 16, 17, 18, 19 and 20 differ from claim 2, 3, 4, 5 and 6 respectively in that they recite a non-transitory computer readable medium including a sequence of instructions which when executed perform the method of claim 2, 3, 4, 5 and 6. For reasons discussed above, the claimed process is directed to mental steps. Use of a non-transitory medium to store instructions which when executed perform the method of claim 2, 3, 4, 5 and 6 constitutes use of a component of a generic computer as a tool and does not constitute an application of significantly more than the abstract idea. Accordingly, claim 16, 17, 18, 19 and 20 are not patent eligible.
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.
Claim 1-4, 6-11, 13-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Knight, Matthew James (PGPUB Document No. 20160180434), hereafter referred as to “Knight”, in view of Altschuler, Steven et al (US Patent No. 6778971), hereafter, referred to as “Altschuler”.
Claim 1, Knight teaches A method, comprising: retrieving, by a computer application executed by a user electronic device for a user, a persona for the user(Knight, para 0013 discloses retrieving user persona for executing search ”the travel service may determine a persona to be assigned to a user search query indirectly, such as by analyzing previous search queries of the user, travel histories of the user, or web browsing activities of the user”), wherein the persona is based on user transactions and/or user inquiries to the computer application(Knight, para 0013 discloses determining user persona based on user transaction or search history ”A user's past travel purchases, travel search history, and other profile information of the user may be examined to determine a relevant persona”);
retrieving, by the computer application and using a personalization system, application features for the computer application that are relevant to the persona(Knight, para 0033 discloses hotel booking application attributes are getting obtained that are relevant to user person “the weighting factors corresponding to a “family vacation” persona may indicate a strong positive preference for hotels near a theme park, a weak positive preference for free parking, and a strong negative preference for hotels near an airport. These weighting factors may be used to determine that the attributes of a hotel (e.g., one with free parking near a theme park) correlate positively with the preferences of the “family vacation” persona”);
retrieving, by the computer application, localized content for the application features(Knight, element 412 “DETERMINE SET OF DISCLOSABLE TRAVEL ITEM ATTRIBUTES” and element 414 “GENERATE OPAQUE TRAVEL ITEM LISTING” discloses retrieving contents for features);
and providing, by the computer application, the entity objects and the localized content to an operating system for the user electronic device; wherein the operating system is configured to surface one of the application features and display the localized content in response to a user search in a search interface provided by the operating system by searching the entity objects, and to control the computer application to present the application feature(Knight, Fig. 3 B and para 0066 discloses displaying application feature (“Walking Distance to Attractions”) and contents (list of hotels) are being displayed in response to user search performed on search interface “Opaque search results 324 and 326 now reflect the top search results identified for a family traveler persona. Opaque search result 324 discloses a hotel near the waterfront with a swimming pool, fitness center, and within walking distance of tourist attractions”).
But Knight does not explicitly teach translating, by the computer application, the application features into entity objects;
However, in the same field of endeavor of forming objects from entity features Altschuler teaches teach translating, by the computer application, the application features into entity objects(Altschuler, Fig. 45 and col 23:24-26 disclose translating or converting entity features into an object “….all attributes are converted to entities using a "has a" relation. (Recall, e.g., FIGS. 8A, 8B, and 9B.)” );
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of forming objects from entity features of Altschuler into retrieval of contents relevant to a persona of Knight to produce an expected result of search and retrieve user persona related contents. The modification would be obvious because one of ordinary skill in the art would be motivated to present different types of objects in a uniform way by converting user data retrieved from various sources into a uniform format(Altschuler, abstract).
Regarding Claim 2, Knight and Altschuler teach all the limitations of claim 1 and Knight further teaches further comprising: receiving, by a backend computer program, a plurality of data points for a plurality of customers; clustering, by the backend computer program, the data points into a plurality of clusters using a clustering algorithm; identifying, by the backend computer program, a persona for each of the clusters; receiving, by the backend computer program, a plurality of user data points for the user(Knight, para 0015 discloses clustering user behavior data and determining persona for cluster “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”);
identifying, by the backend computer program, one of the clusters for the plurality of user data points; and returning, by the backend computer program, the persona for the identified cluster to the computer application(Knight, para 0015 discloses clustering user behavior data and determining persona for cluster “the travel service may analyze data such as travel item purchases, search queries, hotel occupancy rates, and traveler reviews by multiple users corresponding to a persona to dynamically determine a persona's weighting factors based on aggregated activity of a plurality of travelers corresponding to the persona. The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 3, Knight and Altschuler teach all the limitations of claim 2 and Knight further teaches wherein the data points and the user data points comprise average monthly spends, spending categories, spending patterns, financial products owned, benefits/offers exploration/redemption rate, and/or application feature usage(Knight, para 0015 further discloses data points such spending pattern is being used for identifying user persona “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 4, Knight and Altschuler teach all the limitations of claim 2 and Knight further teaches wherein the personas are based on a common feature in each of the clusters(Knight, para 0015 further discloses similarity in common feature such as travel item purchases for a particular age group for a particular duration of time is being used for identifying user persona “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 6, Knight and Altschuler teach all the limitations of claim 2 and Knight further teaches wherein the user data points are limited to a time period (Knight, para 0015 further discloses data points are limited by travel item purchases for a particular age group for a particular duration of time is being used for identifying user persona “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 7, Knight and Altschuler teach all the limitations of claim 1 and Knight further teaches wherein the localized content comprises a description for each of the application features(Knight, Fig. 3 B and para 0066 discloses displaying application feature (“Walking Distance to Attractions”) and contents (list of hotels) are being displayed in response to user search performed on search interface “Opaque search results 324 and 326 now reflect the top search results identified for a family traveler persona. Opaque search result 324 discloses a hotel near the waterfront with a swimming pool, fitness center, and within walking distance of tourist attractions”).
Claim 8, Knight teaches A system, comprising: a user electronic device executing an operating system and a computer application; a computer application executed by a user electronic device; and a backend electronic device executing a backend computer program and a personalization system(Knight, para 0078 discloses a system comprising processors, storages and memories “The steps of a method, process, routine, or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of a non-transitory computer-readable storage medium”) and comprising an application features database and a localized content database(Knight, Fig. 2A and para 0040 disclose a local database/store for travel item contents “query the travel item inventory data store 156 for travel items that are relevant to the travel query search criteria”); wherein: the computer application is configured to retrieve, for a user, a persona for the user (Knight, para 0013 discloses retrieving user persona for executing search ”the travel service may determine a persona to be assigned to a user search query indirectly, such as by analyzing previous search queries of the user, travel histories of the user, or web browsing activities of the user”), wherein the persona is based on user transactions and/or user inquiries to the computer application (Knight, para 0013 discloses determining user persona based on user transaction or search history ”A user's past travel purchases, travel search history, and other profile information of the user may be examined to determine a relevant persona”);
the computer application is configured to retrieve, via the personalization system, application features for the computer application that are relevant to the persona from the application features database (Knight, para 0033 discloses hotel booking application attributes are getting obtained that are relevant to user person “the weighting factors corresponding to a “family vacation” persona may indicate a strong positive preference for hotels near a theme park, a weak positive preference for free parking, and a strong negative preference for hotels near an airport. These weighting factors may be used to determine that the attributes of a hotel (e.g., one with free parking near a theme park) correlate positively with the preferences of the “family vacation” persona”);
the computer application is configured to retrieve localized content for the application features from the localized content database (Knight, element 412 “DETERMINE SET OF DISCLOSABLE TRAVEL ITEM ATTRIBUTES” and element 414 “GENERATE OPAQUE TRAVEL ITEM LISTING” of Fig. 4discloses retrieving contents for features; Fig. 2A and para 0040 further disclose a local database/store for travel item contents “query the travel item inventory data store 156 for travel items that are relevant to the travel query search criteria”);
and the computer application is configured to provide the entity objects and the localized content to the operating system; wherein the operating system is configured to surface one of the application features and display the localized content in response to a user search in a search interface provided by the operating system by searching the entity objects, and to control the computer application to present the application feature (Knight, Fig. 3 B and para 0066 discloses displaying application feature (“Walking Distance to Attractions”) and contents (list of hotels) are being displayed in response to user search performed on search interface “Opaque search results 324 and 326 now reflect the top search results identified for a family traveler persona. Opaque search result 324 discloses a hotel near the waterfront with a swimming pool, fitness center, and within walking distance of tourist attractions”).
But Knight does not explicitly teach the computer application is configured to translate the application features into entity objects;
However, in the same field of endeavor of forming objects from entity features Altschuler teaches teach the computer application is configured to translate the application features into entity objects (Altschuler, Fig. 45 and col 23:24-26 disclose translating or converting entity features into an object “….all attributes are converted to entities using a "has a" relation. (Recall, e.g., FIGS. 8A, 8B, and 9B.)” );
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of forming objects from entity features of Altschuler into retrieval of contents relevant to a persona of Knight to produce an expected result of search and retrieve user persona related contents. The modification would be obvious because one of ordinary skill in the art would be motivated to present different types of objects in a uniform way by converting user data retrieved from various sources into a uniform format(Altschuler, abstract).
Regarding Claim 9, Knight and Altschuler teach all the limitations of claim 8 and Knight further teaches wherein: the backend computer program is configured to receive a plurality of data points for a plurality of customers; the backend computer program is configured to cluster the data points into a plurality of clusters using a clustering algorithm; the backend computer program is configured to identify a persona for each of the clusters; the backend computer program is configured to receive a plurality of user data points for the user(Knight, para 0015 discloses clustering user behavior data and determining persona for cluster “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”);
the backend computer program is configured to identify one of the clusters for the plurality of user data points; and the backend computer program is configured to return the persona for the identified cluster to the computer application (Knight, para 0015 discloses clustering user behavior data and determining persona for cluster “the travel service may analyze data such as travel item purchases, search queries, hotel occupancy rates, and traveler reviews by multiple users corresponding to a persona to dynamically determine a persona's weighting factors based on aggregated activity of a plurality of travelers corresponding to the persona. The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 10, Knight and Altschuler teach all the limitations of claim 9 and Knight further teaches wherein the data points and the user data points comprise average monthly spends, spending categories, spending patterns, financial products owned, benefits/offers exploration/redemption rate, and/or application feature usage (Knight, para 0015 further discloses data points such spending pattern is being used for identifying user persona “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 11, Knight and Altschuler teach all the limitations of claim 9 and Knight further teaches wherein the personas are based on a common feature in each of the clusters(Knight, para 0015 further discloses similarity in common feature such as travel item purchases for a particular age group for a particular duration of time is being used for identifying user persona “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 13, Knight and Altschuler teach all the limitations of claim 9 and Knight further teaches wherein the user data points are limited to a time period (Knight, para 0015 further discloses data points are limited by travel item purchases for a particular age group for a particular duration of time is being used for identifying user persona “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 14, Knight and Altschuler teach all the limitations of claim 8 and Knight further teaches wherein the localized content comprises a description for each of the application features(Knight, Fig. 3 B and para 0066 discloses displaying application feature (“Walking Distance to Attractions”) and contents (list of hotels) are being displayed in response to user search performed on search interface “Opaque search results 324 and 326 now reflect the top search results identified for a family traveler persona. Opaque search result 324 discloses a hotel near the waterfront with a swimming pool, fitness center, and within walking distance of tourist attractions”).
Claim 15, Knight teaches A non-transitory computer readable storage medium, including instructions stored thereon, which when read and executed by one or more computer processors, cause the one or more computer processors to perform steps comprising(Knight, para 0078 discloses a system comprising processors, storages and memories “The steps of a method, process, routine, or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of a non-transitory computer-readable storage medium”): retrieving a persona for a user (Knight, para 0013 discloses retrieving user persona for executing search ”the travel service may determine a persona to be assigned to a user search query indirectly, such as by analyzing previous search queries of the user, travel histories of the user, or web browsing activities of the user”), wherein the persona is based on user transactions and/or user inquiries to a computer application(Knight, para 0013 discloses determining user persona based on user transaction or search history ”A user's past travel purchases, travel search history, and other profile information of the user may be examined to determine a relevant persona”);
retrieving, using a personalization system, application features for the computer application that are relevant to the persona(Knight, para 0033 discloses hotel booking application attributes are getting obtained that are relevant to user person “the weighting factors corresponding to a “family vacation” persona may indicate a strong positive preference for hotels near a theme park, a weak positive preference for free parking, and a strong negative preference for hotels near an airport. These weighting factors may be used to determine that the attributes of a hotel (e.g., one with free parking near a theme park) correlate positively with the preferences of the “family vacation” persona”);
retrieving, localized content for the application features(Knight, element 412 “DETERMINE SET OF DISCLOSABLE TRAVEL ITEM ATTRIBUTES” and element 414 “GENERATE OPAQUE TRAVEL ITEM LISTING” discloses retrieving contents for features); wherein the localized content comprises a description for each of the application features(Knight, Fig. 3 B and para 0066 discloses displaying application feature (“Walking Distance to Attractions”) and contents (list of hotels) are being displayed in response to user search performed on search interface “Opaque search results 324 and 326 now reflect the top search results identified for a family traveler persona. Opaque search result 324 discloses a hotel near the waterfront with a swimming pool, fitness center, and within walking distance of tourist attractions”);
surfacing one of the application features and displaying the localized content in response to a user search in a search interface by searching the entity objects; and presenting to present the application feature (Knight, Fig. 3 B and para 0066 discloses displaying application feature (“Walking Distance to Attractions”) and contents (list of hotels) are being displayed in response to user search performed on search interface “Opaque search results 324 and 326 now reflect the top search results identified for a family traveler persona. Opaque search result 324 discloses a hotel near the waterfront with a swimming pool, fitness center, and within walking distance of tourist attractions”).
But Knight does not explicitly teach translating the application features into entity objects;
However, in the same field of endeavor of forming objects from entity features Altschuler teaches teach translating the application features into entity objects (Altschuler, Fig. 45 and col 23:24-26 disclose translating or converting entity features into an object “….all attributes are converted to entities using a "has a" relation. (Recall, e.g., FIGS. 8A, 8B, and 9B.)” );
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of forming objects from entity features of Altschuler into retrieval of contents relevant to a persona of Knight to produce an expected result of search and retrieve user persona related contents. The modification would be obvious because one of ordinary skill in the art would be motivated to present different types of objects in a uniform way by converting user data retrieved from various sources into a uniform format(Altschuler, abstract).
Regarding Claim 16, Knight and Altschuler teach all the limitations of claim 15 and Knight further teaches further including instructions stored thereon, which when read and executed by the one or more computer processors, cause the one or more computer processors to perform steps comprising: receiving a plurality of data points for a plurality of customers; clustering the data points into a plurality of clusters using a clustering algorithm (Knight, para 0015 discloses clustering user behavior data and determining persona for cluster “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”);
identifying a persona for each of the clusters; receiving a plurality of user data points for the user; and identifying one of the clusters for the plurality of user data points (Knight, para 0015 discloses clustering user behavior data and determining persona for cluster “the travel service may analyze data such as travel item purchases, search queries, hotel occupancy rates, and traveler reviews by multiple users corresponding to a persona to dynamically determine a persona's weighting factors based on aggregated activity of a plurality of travelers corresponding to the persona. The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 17, Knight and Altschuler teach all the limitations of claim 16 and Knight further teaches wherein the data points and the user data points comprise average monthly spends, spending categories, spending patterns, financial products owned, benefits/offers exploration/redemption rate, and/or application feature usage (Knight, para 0015 further discloses data points such spending pattern is being used for identifying user persona “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 18, Knight and Altschuler teach all the limitations of claim 16 and Knight further teaches wherein the personas are based on a common feature in each of the clusters(Knight, para 0015 further discloses similarity in common feature such as travel item purchases for a particular age group for a particular duration of time is being used for identifying user persona “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Regarding Claim 20, Knight and Altschuler teach all the limitations of claim 16 and Knight further teaches wherein the user data points are limited to a time period (Knight, para 0015 further discloses data points are limited by travel item purchases for a particular age group for a particular duration of time is being used for identifying user persona “The travel service may further analyze the activities of multiple users to dynamically determine the personas themselves based on patterns or clusters of user behaviors. For example, the travel service may dynamically identify a “spring break” persona by detecting similarities in the travel item purchases of adults age 18 to 25 in the months of March and April”).
Claim 5, 12 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Knight, Matthew James (PGPUB Document No. 20160180434), hereafter referred as to “Knight”, in view of Altschuler, Steven et al (US Patent No. 6778971), hereafter, referred to as “Altschuler”, in further view of Vulgarakis, Feljan et al (PGPUB Document No. 20230291952), hereafter, referred to as “Vulgarakis”
Regarding Claim 5, Knight and Altschuler teach all the limitations of claim 2 and don’t explicitly teach wherein the clusters are updated periodically.
However, in the same field of endeavor of user clustering Vulgarakis teaches wherein the clusters are updated periodically (Vulgarakis, para 0090 discloses clustering users and updating the clusters periodically “In step S507, in the user profiler, the users are clustered into one or more user clusters and the user clusters are updated periodically”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of updating user clusters periodically of Vulgarakis into clustering users and assignment of persona of each cluster of Knight and Altschuler to produce an expected result of updating clusters to include new data points. The modification would be obvious because one of ordinary skill in the art would be motivated to improve user experience by adding additional contents that are better targeted to a specific user(Vulgarakis, para 0014-0015).
Regarding Claim 12, Knight and Altschuler teach all the limitations of claim 9 and don’t explicitly teach wherein the clusters are updated periodically.
However, in the same field of endeavor of user clustering Vulgarakis teaches wherein the clusters are updated periodically (Vulgarakis, para 0090 discloses clustering users and updating the clusters periodically “In step S507, in the user profiler, the users are clustered into one or more user clusters and the user clusters are updated periodically”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of updating user clusters periodically of Vulgarakis into clustering users and assignment of persona of each cluster of Knight and Altschuler to produce an expected result of updating clusters to include new data points. The modification would be obvious because one of ordinary skill in the art would be motivated to improve user experience by adding additional contents that are better targeted to a specific user(Vulgarakis, para 0014-0015).
Regarding Claim 19, Knight and Altschuler teach all the limitations of claim 16 and don’t explicitly teach wherein the clusters are updated periodically.
However, in the same field of endeavor of user clustering Vulgarakis teaches wherein the clusters are updated periodically (Vulgarakis, para 0090 discloses clustering users and updating the clusters periodically “In step S507, in the user profiler, the users are clustered into one or more user clusters and the user clusters are updated periodically”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the feature of updating user clusters periodically of Vulgarakis into clustering users and assignment of persona of each cluster of Knight and Altschuler to produce an expected result of updating clusters to include new data points. The modification would be obvious because one of ordinary skill in the art would be motivated to improve user experience by adding additional contents that are better targeted to a specific user(Vulgarakis, para 0014-0015).
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered pertinent to applicant’s disclosure.
Aulie, Simen (US 12541557 ) -teaches persona based modeling systems and techniques, a user interface is displayed having a plurality of representations of a plurality of personas, each persona of the plurality of personas modeling one or more user characteristics.
Bar, Eliyahu (US 20250111154) -teaches cluster information regarding financial transaction clusters generated by the clustering engine 160 (including the financial transaction vector center and the vendor vector center of the clusters), and identified vendor mis categorizations.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABDULLAH A DAUD whose telephone number is (469)295-9283. The examiner can normally be reached M~F: 9:30 am~6:30 pm.
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, Amy Ng can be reached at 571-270-1698. 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.
/ABDULLAH A DAUD/Examiner, Art Unit 2164 /AMY NG/Supervisory Patent Examiner, Art Unit 2164
Prosecution Insights