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 .
DETAILED ACTION
The present invention application contains 20 claims. Claims 1, 19 and 20 are independent. Claims 1-20 are examined and rejected by the following detail action.
Examiner Notes
The prior art rejections below cite particular paragraphs, columns, and/or line numbers in the references for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art.
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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-2 and 4-20 are rejected under 35 U.S.C. 103 as being unpatentable over Donsbach et al. (“Donsbach”, US Patent. 8122020 B1) in view of O’Konski et al. (“O’Konski”, US PG-Pub. 2015/0268800 A1).
Re-claim 1,
Donsbach teaches a computing system comprising:
at least one processor; and at least one non-transitory computer-readable medium (Fig. 5, col. 8 lines [40-54]. Donsbach describes the system using at least one computer 88 which includes a processor and hardware memory or medium to implement tagging and recommendation ) comprising program instructions that are executable by the at least one processor such that the computing system is configured to:
receive, for a first account in a plurality of accounts of a media service, an indication of at least one first sample media item to be associated with a particular category (Figs. 1, 5, col. 5 lines [40-67], col. 9 lines [4-15]. Donsbach describes the Tagging Service 98 maintains a database 100 of user-specific tag data in which each user (as a first user or account) selects a catalog item (as first sample media) to associate with a tag (as category) through the tagging interface. The tagging service maintains separate tag-item ID pairs for every user. Identical tags created by two users are treated as distinct user specific record, thereby maintaining each user’s respective item/category association. For example, user selects the “Add” button 34 to associate a catalog item (as first sample media) with a particular tag 36 (i.e. Karsten, Italian or gift, etc. tags as categories));
receive, for a second account in the plurality of accounts of the media service, an indication of at least one second sample media item to be associated with the particular category, wherein the at least one first sample media item is different from the at least one second sample media item (Figs. 1, 5, col. 5 lines [40-67], col. 9 lines [4-15]. Donsbach describes the Tagging Service 98 maintains a database 100 of user-specific tag data in which each user (as a second user or account) selects a catalog item (as second sample media) to associate with a tag (as category) through the tagging interface. The tagging service maintains separate tag-item ID pairs for every user. Identical tags created by two users are treated as distinct user specific record, thereby maintaining each user’s respective item/category association. For example, user selects the “Add” button 34 to associate a catalog item (as second sample media) with a particular tag 36 (i.e. Karsten, Italian or gift, etc. tags as categories). Because the users independently select items, the first and second users may associate different items with the identical category label);
associate, for the first account, the at least one first sample media item with the particular category (Figs. 1, 5, col. 5 lines [40-67], col. 9 lines [4-15]. Donsbach describes the concept of associating the sample media item with a particular category when user selects the “Add” button 34 to associate a catalog item (as a first sample media item) with a particular tag 36 (i.e. Karsten, Italian or gift, etc. tags as categories) for the first user account);
associate, for the second account, the at least one second sample media item with the particular category (Figs. 1, 5, col. 5 lines [40-67], col. 9 lines [4-15]. Donsbach describes the concept of associating the sample media item with a particular category when user selects the “Add” button 34 to associate a catalog item (as a second sample media item) with a particular tag 36 (i.e. Karsten, Italian or gift, etc. tags as categories) for the second user account);
based on the association between the particular category and the at least one first sample media item, provide for the first account at least one first media content recommendation for the particular category (Figs. 2-6, col. 7 lines [4-21], col. 8 lines [4-28], col. 9 lines [24-43]. Donsbach describes the recommendations can be obtained or generated based on the tag products (as first sample media item for first user account or user) associated with the particular category or user tag (i.e. Karsten as first user or account tag category), tag-based or content-based similarities item-to-item mapping that may include the tagged products (i.e. each tagged product 62 as the first sample media item) when user checks the rating functionality 64 to consider the tagged products as part of generated recommendation described in Fig. 4, col. 8 lines [4-28]); and
based on the association between the particular category and the at least one second sample media item, provide for the second account at least one second media content recommendation for the particular category, wherein the at least one second media content recommendation is different from the at least one first media content recommendation (Figs. 2-6, col. 7 lines [4-21], col. 8 lines [4-28], col. 9 lines [24-43]. Donsbach describes the recommendations can be obtained or generated based on the tag products (as second sample media item for second user account or user) associated with the particular category or user tag (i.e. Karsten as second user or account tag category), tag-based or content-based similarities item-to-item mapping that may include the tagged products (i.e. each tagged product 62 as the first sample media item) when user checks the rating functionality 64 to consider the tagged products as part of generated recommendation described in Fig. 4, col. 8 lines [4-28]. Because the users independently select items, the first and second users may associate different items with the identical category label and the tagged item may be part of generated recommendation when user selecting the rating functionality 64 that implicitly indicates the at least second media content recommendation is different from the at least one first media content recommendation based on the included preference or seeded sample media that was initially different).
Donsbach does not expressly teach wherein the at least one second media content recommendation is different from the at least one first media content recommendation.
However, O’Konski teaches:
wherein the at least one second media content recommendation is different from the at least one first media content recommendation (Figs. 1, 2, 5, [0021]. O’Konski describes the process of generating personalized playlist based on each user’s respective collection, selected tracks, favorites and other preference data. It would have been obvious to provide different playlists when users supply different seed tracks or have different personal media collections).
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the multi-user recommendation service teaching of Donsbach with the personalized playlist generation from user media tracks, classification and preference information teaching of O’Konski to improve relevance of recommendation playlists by limiting each category-specific recommendation to media characteristic demonstrated by the particular user’s selected samples.
Re-claim 2,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein the particular category comprises one or more of: an activity, a mood, or a playback context (Figs. 2, 3, col. 7 lines [18-21]. Donsbach describes the particular category is an activity (i.e. Travel)).
Re-claim 4,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein associating the particular category with the respective at least one first sample media item comprises storing an association between the first account, the particular category and the respective at least one first sample media item (Fig. 5, col. 1 lines [63-66]. Donsbach describes “…The tags and tag-item assignments created by each user are stored persistently in association with the user and may be kept private to the user or exposed to others.”).
Re-claim 5,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein associating the particular category with the respective at least one first sample media item comprises storing an association between the particular category and an identifier corresponding to the respective at least one first sample media item (Fig. 5, col. 1 lines [63-66], col. 9 lines [4-7]. Donsbach describes “…The tags and tag-item assignments created by each user are stored persistently in association with the user and may be kept private to the user or exposed to others.” and “… a Tagging Service 98 that maintains a database 100 of user-specific tag data. The tag data stored for each user may, for example, include a set of tag-item ID pairs”).
Re-claim 6,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein associating the particular category with the respective at least one first sample media item comprises: causing a remote computing device to store an association between the particular category and the respective at least one first sample media item (Fig. 5, col. 1 lines [63-66], col. 8 lines [51-54]. Donsbach describes “…The tags and tag-item assignments created by each user are stored persistently in association with the user and may be kept private to the user or exposed to others.” and “… FIG. 5, the system 86 comprises web servers 90 which process HTTP (Hypertext Transfer Protocol) requests received over the Internet from the user computers 88 that run web browser software.”).
Re-claim 7,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein providing the at least one first media content recommendation comprises displaying, via a graphical display associated with the first account, at least one graphical representation corresponding to the at least one first media content recommendation (Fig. 3, col. 7 lines [4-21, 56-58], col. 9 lines [24-43]. Donsbach describes the recommendation can be obtained and displayed0 on the web page 50’s user interface shown in Fig. 3 based on the tag products (as first sample media item for first user account or user) associated with the particular category or user tag (i.e. Karsten as first user or account tag category), tag-based or content-based similarities item-to-item mapping).
Re-claim 8,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein providing the at least one first media content recommendation comprises causing at least one media item associated with the at least one first content recommendation to be added to a purchase queue of the first account.
(Fig. 3, col. 7 lines [56-63]. Donsbach describes the recommendation’s media items can be added to first user’s account purchase queue (i.e. wish list, shopping cart, wedding registry, etc.) ).
Donsbach fails to teach a playback queue.
However, O’Konski teaches a playback queue (Fig. 3, [0037, 0044]. O’Konski describes the concept of user adding or removing the media tracks from a personalized playlist queue 312).
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the multi-user recommendation service teaching of Donsbach with the personalized playlist generation from user media tracks, classification and preference information teaching of O’Konski to improve relevance of recommendation playlists by limiting each category-specific recommendation to media characteristic demonstrated by the particular user’s selected samples.
Re-claim 9,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein providing the at least one first media content recommendation comprises causing at least one media item associated with the at least one first content recommendation to be added to a purchase queue of the first account, the purchase queue associated with the particular category (Fig. 3, col. 7 lines [56-63]. Donsbach describes the tag-specific recommendation’s media items (i.e. “Karsten” as an associated particular category) can be added to first user’s account purchase queue (i.e. wish list, shopping cart, wedding registry, etc.) ).
Donsbach fails to teach a playlist.
However, O’Konski teaches a playlist (Fig. 3, [0037, 0044]. O’Konski describes the personalized playlist queue 312).
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the multi-user recommendation service teaching of Donsbach with the personalized playlist generation from user media tracks, classification and preference information teaching of O’Konski to improve relevance of recommendation playlists by limiting each category-specific recommendation to media characteristic demonstrated by the particular user’s selected samples.
Re-claim 10,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein the at least one first media content recommendation comprises at least one media item, and the at least one media item has at least one characteristic in common with the at least one first sample media item (Fig. 3, col. 9 lines [24-43]. Donsbach describes the tag-specific recommendation’s media items including the tag-based or content-based similarities item-to-item mapping (as characteristic in common or similarities).
Re-claim 11,
Donsbach-O’Konski teaches the system in claim 1, but Donsbach fails to teach the system, wherein providing the at least one first media content recommendation comprises playing back, via at least one playback device associated with the first account, at least one media item corresponding to the at least one first media content recommendation.
However, O’Konski teaches:
wherein providing the at least one first media content recommendation comprises playing back, via at least one playback device associated with the first account, at least one media item corresponding to the at least one first media content recommendation (Figs. 3, 5, [0050]. O’Konski describes the generated user personalized playlist queue 312 can be playback shown in block 515).
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the multi-user recommendation service teaching of Donsbach with the personalized playlist generation from user media tracks, classification and preference information teaching of O’Konski to improve relevance of recommendation playlists by limiting each category-specific recommendation to media characteristic demonstrated by the particular user’s selected samples.
Re-claim 12,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein the program instructions include instructions that are executable to configure the computer system to:
receive, from a third account in the plurality of accounts of the media service, an indication of at least one third sample media item to be associated with the particular category, wherein the at least one third sample media item is different from the at least one first sample media item (Figs. 1, 5, col. 5 lines [40-67], col. 9 lines [4-15]. Donsbach describes the Tagging Service 98 maintains a database 100 of user-specific tag data in which each user (as a third user or account) selects a catalog item (as third sample media) to associate with a tag (as category) through the tagging interface. The tagging service maintains separate tag-item ID pairs for every user. Identical tags created by two users are treated as distinct user specific record, thereby maintaining each user’s respective item/category association. For example, user selects the “Add” button 34 to associate a catalog item (as third sample media) with a particular tag 36 (i.e. Karsten, Italian or gift, etc. tags as categories). Because the users independently select items, the first and third users may associate different items with the identical category label);
associate, for the third account, the at least one this sample media item with the particular category (Figs. 1, 5, col. 5 lines [40-67], col. 9 lines [4-15]. Donsbach describes the concept of associating the sample media item with a particular category when user selects the “Add” button 34 to associate a catalog item (as a third sample media item) with a particular tag 36 (i.e. Karsten, Italian or gift, etc. tags as categories) for the third user account); and
based on the association between the particular category and the at least one third sample media item, provide for the third account at least one third media content recommendation for the particular category (Figs. 2, 3, 5, 6, col. 7 lines [4-21], col. 9 lines [24-43]. Donsbach describes the recommendations can be obtained or generated based on the tag products (as third sample media item for third user account or user) associated with the particular category or user tag (i.e. Karsten as third user or account tag category), tag-based or content-based similarities item-to-item mapping);
wherein the at least one third media content recommendation is the same as the at least one first media content recommendation (Figs. 2, 3, 5, 6, col. 7 lines [4-21], col. 9 lines [24-43], col. 11 lines [18-32]. Donsbach describes the recommendations can be obtained or generated based on the tag products associated with the particular category or user tag (i.e. Karsten as first and third user or account tag category), tag-based or content-based similarities item-to-item mapping that are stored in shared Similar Items Table 104. Donsbach explains that the retrieve list may contain “like items” that scores of like items are combined shown in block 76 and that a particular item may be related to two or more different tagged items. Accordingly, different tagged input items (as first and third account tagged input items) can identify a common related item).
Re-claim 13,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, wherein providing the at least one first media content recommendation comprises providing the at least one first media content recommendation based on an event associated with the first account and the particular category (Fig. 3, col. 1 lines [44-46]. Donsbach describes the system enables users to request recommendations that are specific to a predefined item category (e.g., travel event, gift registry for particular event)).
Re-claim 14,
In addition to what Donsbach-O’Konski teaches the system in claim 13, Donsbach also teaches the system, wherein the event comprises a selection, via a user interface associated with the first account, of a graphical representation corresponding to the particular category (Fig. 3, col. 17 lines [07-10]. Donsbach describes “… the user can click on the link/tag labeled "Karsten" to access a web page (see ) which displays product recommendations that are specific to this tag.”).
Re-claim 15,
Donsbach-O’Konski teaches the system in claim 13, but Donsbach fails to teach the system, wherein the event comprises a detection of an activity associated with the particular category.
However, O’Konski teaches:
wherein the event comprises a detection of an activity associated with the particular category (Figs. 1-2, [0018, 0033, 0036]. O’Konski describes the playlist can be generated to match a user’s mood or activity level. The Playlist-generation unit 204 uses the detected activity (i.e. walking, driving, jogging, etc. using motion detector, GPS, heart-rate data or other biorhythmic information) when generating the personalized playlist).
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the multi-user recommendation service teaching of Donsbach with the personalized playlist generation from user media tracks, classification and preference information teaching of O’Konski to improve relevance of recommendation playlists by limiting each category-specific recommendation to media characteristic demonstrated by the particular user’s activity event.
Re-claim 16,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, further comprising: before receiving the indication of at least one sample media item to be associated with the particular category from each account in a plurality of accounts, transmit, to each account in the plurality of accounts, a list of categories comprising at least the particular category (Figs. 1, 5, col. 5 lines [16-19]. Donsbach describes “…the web site system may provide a set of commonly used tags, such as “family”, " "gift," "vacation," etc.--or associated images and/or sounds--from which the user may choose to tag a particular item”).
Re-claim 17,
In addition to what Donsbach-O’Konski teaches the system in claim 1, Donsbach also teaches the system, further comprising: before receiving the indication of at least one sample media item to be associated with the particular category from each account in a plurality of accounts, cause respective user interfaces of each account in the plurality of accounts to display a graphical representation corresponding to the particular category (Figs. 1, 5, col. 5 lines [55-67]. Donsbach describes the website displaying the list of categories or tags 36).
Re-claim 18,
In addition to what Donsbach-O’Konski teaches the system in claim 17, Donsbach also teaches the system, wherein receiving the indication of at least one sample media item comprises receiving the indication via the graphical representation (Fig. 1, col. 5 lines [40-67]. Donsbach describes the user can tag a catalog item (as a sample media) with a particular tag 36 (i.e. Karsten, Italian or gift, etc. tags as categories)).
Re-claim 19,
claim 19 is a method claim having similar limitations in scope of claim 1; therefore, it is rejected under similar rationale.
Re-claim 20,
claim 20 is a medium claim having similar limitations in scope of claim 1; therefore, it is rejected under similar rationale.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Donsbach in view of O’Konski, and further in view of Liusaari et al. (“Liusaari”, US PG-Pub. 2022/0374196 A1).
Re-claim 3,
Donsbach-O’Konski teaches the system in claim 2, but Donsbach fails to teach the system, wherein the playback context is determined based on one or more of: a playback device via which media content is to be played back, a location in which media content is to be played back, or a time at which media content is to be played back.
However, Liusaari teaches:
wherein the playback context is determined based on one or more of: a playback device via which media content is to be played back, a location in which media content is to be played back, or a time at which media content is to be played back (Figs. 3, 13, Abstract. Liusaari describes the concept of the playback context based on locations, time, devices, event, etc.).
Therefore, it would have been obvious to one having the ordinary skill in the art before the effective filing date of the claimed invention to modify the multi-user recommendation service teaching of Donsbach with the method of associating media content with playback contexts teaching of Liusaari to provide a simple graphical mechanism for specifying the category with which the user’s selected media track is to be associated for later automatically playback by detected context.
Conclusion
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/TUAN S NGUYEN/Primary Examiner, Art Unit 2179
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