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 .
This Office Action has been issued in response to Applicant’s Communication of application S/N 18/949,764 filed on November 15, 2024. Claims 2 to 22 are currently pending with the application.
Priority
The instant application is a Continuation of application S/N 17/458,137, filed on August 8 26, 2021, now U.S. Patent No. 12,189,682, and which claims priority from provisional application S/N 63/071,269, filed on August 27, 2020. Applicant’s claim for the benefit of the prior-filed applications under 35 U.S.C. 119(e), 120, 121, or 365(c), or 386(c) is acknowledged.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 10/27/2025 was filed before the mailing date of the first action on the merits. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Examiner’s Note
Examiner respectfully points out that claims 8, 15, and 22 recite the contingent limitations “the music recommendation request is automatically generated in response to detecting access…”. The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the conditions precedent are not met (See MPEP 2111.04(II)). Therefore, since claim 8 is a method claim, the contingent limitations recited above are not required in claim 8. Nonetheless, and in the interest of compact prosecution, all the limitations have been considered as if they are positively recited.
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.
Claims 2, 4, 8, 9, 11, 15, 16, 18, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Iyengar et al. (U.S. Publication No. 2015/0052554) hereinafter Iyengar, and further in view of Svendsen et al. (U.S. Publication No. 2012/0054233) hereinafter Svendsen.
As to claim 2:
Iyengar discloses:
A computer-implemented method, comprising:
automatically generating a music recommendation request for new music recommendations on behalf of a user, wherein the music recommendation request indicates a current user location [Paragraph 0018 teaches recommendations may include music playlists; Paragraph 0041 teaches content may be media content such as video, audio, or image content; Paragraph 0045 teaches a request to perform media content recommendation analysis may be automatically generated based on a triggering event; Paragraph 0159 teaches identifying a geographic location associated with the request; Paragraph 0173 teaches content may include music or movies];
identifying a location profile based on the current user location [Paragraph 0077 teaches determining that a user is accessing the system from a particular location, and activating geographic viewing profile; Paragraph 0083 teaches each geographic viewing profile may be associated with a geographic context that identifies location information for activating the profile, therefore, based on the detected location of the user, the geographic viewing profile is identified];
processing the location profile through a trained machine learning algorithm to identify a set of songs associated with the current user location, and a set of user profiles corresponding to a set of users [Paragraph 0067 teaches recommendation engine may be used to provide media content recommendations, and to perform a machine learning algorithm; Paragraph 0083 teaches each geographic viewing profile is associated with viewing pattern information that identifies the types of content that have been viewed in association with the identified location or area and the types of content for recommending for viewing at the identified location or area, and may also be associated with particular content recommendations created at least in part based on the geographic context and viewing profile; Paragraph 0138 teaches analyzing geographic viewing profiles associated with other content management accounts to identify relevant content recommendations];
identifying one or more relevant new songs from the set of songs associated with the current user location and the set of user profiles, wherein the one or more relevant new songs are identified based on the music recommendation request and a user profile corresponding to the user [Paragraph 0023 teaches matching a user’s historical content interaction to the factorized historical interactions of other uses, and based in part on this matching, producing a list of media content items to recommend to the user; Paragraph 0060 teaches content recommendations are personalized according to the viewing history and content preferences of the content management account; Paragraph 0139 teaches identifying one or more items to recommend for presentation, including identifying content items that a viewer associated with a particular content management account is likely to enjoy at a particular location, and recommending these content items to a viewer who accesses the media system from the particular location];
presenting the one or more relevant new songs through a user interface associated with the user, wherein the user interface is executed at the current user location [Paragraph 0031 teaches as the user accesses the media system from each of these viewing locations, the system may determine the viewer’s location in real time and use this information to inform the content recommendation engine to alter the content items recommended to the user, therefore, the content items are presented in a user interface executed at the current user location; Paragraph 0125 teaches recommendations are transmitted for presentation at a client machine; Paragraph 0142 teaches providing the identified content recommendations by transmitting the content recommendations to a client machine for presentation in a user interface];
receiving feedback associated with the one or more relevant new songs, wherein the feedback includes interactions with the one or more relevant new songs through the user interface [Paragraph 0026 teaches receiving real-time or near real-time inputs from the user, and translating the feedback into adjustments to the current list of recommendations; Paragraph 0054 teaches receiving information of interactions of the users with the recommended media content items, where the information may be used as positive or negative feedback associated with the recommendations]; and
creating associations amongst the current user location and the one or more relevant new songs, wherein the associations are created by updating the location profile and a set of song profiles corresponding to the one or more relevant new songs according to the feedback and as the feedback is received [Paragraph 0029 teaches geographic context viewing profiles may be created based on a set of geographically-relevant data points related to where content has been viewed in the past, and then, recent geographic context information collected from a client machine may be used to inform and refine recommendations for subsequent content recommendations, where these content recommendations may be provided to the end-user based on the user’s location by creating a series of geo-relevant viewing profiles or models of behavior, in other words, associations between content items and locations are generated and maintained, where the geographic profiles are also updated based on feedback and interaction information; Paragraph 0026 teaches receiving real-time or near real-time inputs from the user, and translating the feedback into adjustments to the current list of recommendations; Paragraph 0047 teaches preference and viewing history for media content, including content items viewed, preferences, the number of times a content item or category was viewed, a location at which a content item was viewed, and the device or devices at which a content item was viewed; Paragraph 0054 teaches receiving new media content preferences or viewing history information, and using the information to update preference data and viewing history data for the media contents, where the data may include a location at which a content item was viewed, a number of times a content item or category was viewed, etc. (paragraph 0047), therefore, including updating the location profile and a set of content profiles corresponding to the contents, and according to the feedback].
Iyengar does not appear to expressly disclose identify a set of user profiles corresponding to a set of users known to share music from the current user location.
Svendsen discloses:
identify a set of user profiles corresponding to a set of users known to share music from the current user location [Paragraph 0008 teaches identifying correlated users based on seed information and user preferences of the requester, where the seed information indicates a current location of the requester, where the media items are tagged with corresponding time and location data indicating the time and location of play; Paragraph 0032 teaches mining play histories of correlated user accounts to generate media recommendations of items matching the user device’s current location].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Iyengar, by identify a set of user profiles corresponding to a set of users known to share music from the current user location, as taught by Svendsen [Paragraph 0008, 0032], because both applications are directed to generating media recommendations; identifying users known to share or play music from the current user location enables to improve the recommendations provided to the users, by taking into consideration the fact that the music tastes of a user may be influenced by his or her geographic location when generating playlists, therefore, enabling the generation of more accurate recommendations (See Svendsen Para [0007]).
As to claim 4:
Iyengar discloses:
generating one or more targeted promotions corresponding to the current user location, wherein the one or more targeted promotions are generated based on the location profile and the set of user profiles [Paragraph 0032 teaches the media system may receive, analyze, and use geographic context information such as the geo-location of prior content views, the geo-location of ongoing content views, and current user locations, where content recommendations can be used in real-time in combination with geo-location information to provide targeted or sponsored advertising or information, for example, while traveling for vacation the user may be presented with media content from the local tourism bureau or local restaurants and businesses in the form of either sponsored content or promotional materials relevant to their “vacation” status and their geographic location].
Same rationale applies to claims 9, 11, 15, 16, 18, and 22, since they recite similar limitations, and are therefore, similarly rejected.
As to claim 8:
Iyengar discloses:
the music recommendation request is automatically generated in response to detecting access to the user interface at the current user location [Paragraph 0045 teaches a request to perform media content recommendation analysis may be automatically generated based on a triggering event; Paragraph 0157 teaches a request for content recommendation is received, where the request may be generated in response to a connection event in which communication between the media content system and a media presentation device is initiated].
Claims 3, 10, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Iyengar et al. (U.S. Publication No. 2015/0052554) hereinafter Iyengar, in view of Svendsen et al. (U.S. Publication No. 2012/0054233) hereinafter Svendsen, and further in view of Cross et al. (U.S. Publication No. 2009/0125499) hereinafter Cross.
As to claim 3:
Iyengar discloses all the limitations as set forth in the rejections of claim 2 above, but does not appear to expressly disclose transmitting the music recommendation request, wherein when the music recommendation request is received by the set of users, newly generated responses are provided by a subset of the set of users; and evaluating the newly generated responses to present additional relevant new songs provided by one or more users from the subset.
Cross discloses:
transmitting the music recommendation request, wherein when the music recommendation request is received by the set of users, newly generated responses are provided by a subset of the set of users [Paragraph 0009 teaches receiving queries from a mobile device and intelligently distributing the queries among users that are deemed suitable to provide useful insight to the queries; Paragraph 0015 teaches selected users provide responses to the queries]; and
evaluating the newly generated responses to present additional relevant new songs provided by one or more users from the subset [Paragraph 0015 teaches responses provided by the selected users are received by the system prior to distribution back to the user that submitted the query].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Iyengar, by transmitting the music recommendation request, wherein when the music recommendation request is received by the set of users, newly generated responses are provided by a subset of the set of users; and evaluating the newly generated responses to present additional relevant new songs provided by one or more users from the subset, as taught by Cross [Paragraph 0009, 0015], because the applications are directed to generating improved user recommendations; providing the recommendation requests to users, and evaluating newly generated responses to provide additional recommendations to the user enables to provide an additional measures through which to identify recipient users to whom to present user queries, and a pathway to control/enhance the caliber of responses and thus, improve user usability and friendliness, and therefore, further enriching user experiences (See Cross Para [0021]).
Same rationale applies to claims 10 and 17, since they recite similar limitations.
Claims 5, 6, 12, 13, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Iyengar et al. (U.S. Publication No. 2015/0052554) hereinafter Iyengar, in view of Svendsen et al. (U.S. Publication No. 2012/0054233) hereinafter Svendsen, and further in view of Alexandersson et al. (U.S. Publication No. 2015/0067509) hereinafter Alexandersson.
As to claim 5:
Iyengar discloses all the limitations as set forth in the rejections of claim 2 above, but does not appear to expressly disclose wherein the feedback includes an indication that playback of a song from the one or more relevant new songs was performed over at least a minimum period of time.
Alexandersson discloses:
wherein the feedback includes an indication that playback of a song from the one or more relevant new songs was performed over at least a minimum period of time [Paragraph 0027 teaches measuring the time before the user skips the music track, where a threshold may be set as for example, 80% or more of the music track has been played before the user skips; Paragraph 0037 teaches measuring a time period indicative of the length of the music track played back before the user skips the music track].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Iyengar, by incorporating feedback that includes an indication that playback of a song from the one or more relevant new songs was performed over at least a minimum period of time, as taught by Alexandersson [Paragraphs 0027, 0037], because the applications are directed to providing information to users; by detecting additional kinds of feedback provided by the users to the provided items, the quality of recommendations provided to the user is improved (See Alexandersson Para [0005], [0030]).
As to claim 6:
Iyengar discloses all the limitations as set forth in the rejections of claim 2 above, but does not appear to expressly disclose wherein the feedback includes an indication that a song from the one or more relevant new songs was saved to a playlist.
Alexandersson discloses:
wherein the feedback includes an indication that a song from the one or more relevant new songs was saved to a playlist [Paragraph 0032 teaches user interactions with a music track include that the user adds the music track as a favorite track in a list of favorites, therefore, saving the song to a playlist].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Iyengar, by incorporating feedback that includes an indication that a song from the one or more relevant new songs was saved to a playlist, as taught by Alexandersson [Paragraphs 0027, 0032], because the applications are directed to providing information to users; by detecting additional kinds of feedback provided by the users to the provided items, the quality of recommendations provided to the user is improved (See Alexandersson Para [0005], [0030]).
Same rationale applies to claims 12, 13, 19, and 20, since they recite similar limitations, and are therefore, similarly rejected.
Claims 7, 14, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Iyengar et al. (U.S. Publication No. 2015/0052554) hereinafter Iyengar, in view of Svendsen et al. (U.S. Publication No. 2012/0054233) hereinafter Svendsen, and further in view of LEE et al. (U.S. Publication No. 2014/0222986) hereinafter Lee.
As to claim 7:
Iyengar discloses all the limitations as set forth in the rejections of claim 2 above, but does not appear to expressly disclose presenting rationales corresponding to the one or more relevant new songs, wherein a rationale corresponding to a relevant new song indicates that the relevant new song was presented based on the current user location.
Lee discloses:
presenting rationales corresponding to the one or more relevant new songs, wherein a rationale corresponding to a relevant new song indicates that the relevant new song was presented based on the current user location [Paragraph 0118 teaches inserting recommendation reasons such as “recommending music you listened to often in the past but have not listened to recently”; Paragraph 0147 teaches generate or select a recommendation reason based on a date when a content provided by a service is generated, time and location, a user’s use history of content, etc., therefore, including a reason based on the current user location].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Iyengar, by presenting rationales corresponding to the one or more relevant new songs, wherein a rationale corresponding to a relevant new song indicates that the relevant new song was presented based on the current user location, as taught by Lee [Paragraphs 0118, 0147], because the applications are directed to providing information to users; presenting explanations or reasons for the recommendations to the users improves the user experience by providing additional information, enabling thereby the further understanding of the provided recommendations.
Same rationale applies to claims 14, and 21, since they recite similar limitations, and are therefore, similarly rejected.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAQUEL PEREZ-ARROYO whose telephone number is (571)272-8969. The examiner can normally be reached Monday - Friday, 8:00am - 5:30pm, Alt Friday, EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sherief Badawi can be reached at 571-272-9782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RAQUEL PEREZ-ARROYO/Primary Examiner, Art Unit 2169
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