DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
Preliminary Amendment
According to the amendment filed 09/24/20225, claims 2-22 have been added, claim 1 has been canceled. Claims 2-22 are pending.
Examiner’s Note
It is noted that non-functional descriptive material does not patentably distinguish over prior art that otherwise renders the claims unpatentable. See for example, MPEP 2111.05, MPEP 2112.01(III). See also In re Ngai, 367 F.3d 1336, 1339 (Fed. Cir. 2004); Exparte Nehls, 88 USPQ2d 1883, 1887-90 (BPAI 2008) (precedential) (discussing cases pertaining to non-functional descriptive material) see also BPAI’s decision in Appeal 2009-010851 (for Ser. No. 10/622,876) or BPAI’s decision in Appeal 2011-011929 (for Ser. No. 11/709,170), pages 6-7. In this case, a particular type of data such as “live content”, “interactive games”, “Internet web pages”, “social connection”, “interactive application”… could be considered as non-functional descriptive material and are not required to give patentable weight because these particular types of data do not functionally change the structure or operation of a system of customize list for different types of data/content.
The limitations “live content”, “interactive games”, “Internet web pages”, “social connection”, “interactive application” are only given patentable weight of types of data or types of connection.
Although non-functional descriptive material are not required to be considered, all claim limitations including non-functional descriptive material are known by prior art as discussed below.
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 pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 2-22 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Bovenschulte et al. (US 20070136753) in view of Sharma et al. (US 7720720).
Note: all documents that are directly or indirectly incorporated by references in their entireties in Bovenschulte (see paragraphs 0035, 0096) including 20050149964 (referred to as Thomas), 20020056087 (referred to as Berezowski), Ser. No. 09/860892 or in Sharma (col. 6, lines 35-39) are respectively treated as part of the specification of Bovenschulte or Sharma (see for example, MPEP 2163.07 b).
Regarding claim 2, Bovenschulte discloses a computer-implemented method of providing one or more content recommendations, the method comprising:
collecting, via one or more servers in communication with a plurality of client devices, content utilization data from the plurality of client devices associated with a plurality of users indicative of a utilization history of the plurality of users (obtaining, via one or more distribution facility (104) and/or audience measurement server (150) in communication with a plurality of user equipment (110-1, 110-N), content utilization data of a plurality of user equipment associated with a plurality of users/audiences indicative a utilization history such as interactions of users/audiences – see include, but are not limited to, figures 1, 4, 10, paragraphs 0011-0013, 0015, 0034, 0042);
analyzing, by at least one application server, the content utilization data to identify a set of popular content items among the plurality of content items by assigning a rating/weight/scale to each content item (analyzing, by at least one audience measurement application at server, the content utilization data to identify popular or high demand content items among the plurality of content items by assigning a star, point to each content item– see include, but are not limited to, figures 10-13, paragraphs 0046, 0048-0049, 0092-0093);
creating a list of the set of popular content items by ranking the ranked/rating content items (creating a list of popular content items by ranking the ranked/rating content items based popularity ratings information – see include, but are not limited to, paragraphs 0035, 0037, 0055, 0093-0094, 0101-0103);
obtaining profile data stored in the at least one application server and associated with a target user, wherein the profile data comprises a content viewing history and patterns of the target user (obtaining profile data stored in at least one application server including audience measurement server and associated with a target user for recommendations, wherein the profile data comprises a content viewing history such as user selection, location, etc. and patterns/habit/behaviors including time of interaction, interaction type, viewing/recording episodes of a series, user frequently view a particular program guide screen and often select advertisement that appear on that particular screen, etc. – see include, but are not limited to, figures, paragraphs 0013-0017, 0039-0040, 0042, 0049, 0102, 0107; Thomas: figures 6-7, 9, paragraphs 008-009, 0055, 0062, 0070) ;
generating a customized list of recommended content items for the target user (generating a customized list of recommended content items/top programs at particular time frame, location, etc. for the target user – see include, but are not limited to, paragraphs 0101-0102; Thomas: figures 10a, 11, paragraph 0070) wherein the customized list of recommended content items is continuously updated (the customized list of top programs/items is continuously updated based user interaction, times, etc. – see include, but are not limited to, paragraphs 0101-0102; Thomas: figures 10a, 11, paragraph 0070); and
transmitting, by a communication module and over a communications network, the customized list of recommended content items to a client device of the target user to play on the client device (transmitting, by a communication module and over a communications network (116,136) the customized list of the top items/programs to a user equipment of the target user/audience to play on the user equipment - see include, but are not limited to, Bovenschulte: figures 1, 10, 14; paragraphs 0101-0102; Thomas: figures 10a, 11, paragraph 0070).
Bovenschulte does not explicitly disclose assigning a score to each content item and ranking the scored content item.
Additionally and/or alternatively, Sharma discloses a method of providing one or more content recommendation, the method comprising:
analyzing, by at least one application server, content utilization data to identify a set of popular content items among the content items by assigning a score to each content item (analyzing, by at least one application including server (211) of recommendation system 10, content utilization data of order history (12/251), recommendation context (16/209) to identify popular items among the items by assigning score to each item – see include, but are not limited to, figures 1-3, col. 3, lines 1-20, col. 5, lines 25-45, 60-64, col. 6, line 65-col. 7, line 12);
creating a list of the set of popular content items by ranking the scored content items (creating a list of recommended items that have the best chance of being accepted by user based on scored recommended items – see include, but are not limited to, figures 2-3, col. 3, lines 1-15, col. 5, lines 1-45, 60-64, col. 6, line 65-col. 7, line 12, col. 10, lines 50-67, col. 13, lines 30-38, col. 14, lines 5-35; Berezowski: figures 14, 11);
obtaining profile data stored in at least one application server and associated with a target user, wherein the profile data comprising a content viewing history and patterns of the target user (obtain a profile data stored in profile database 42/256 of at least one server and associated with a target user/target profile, wherein the profile data comprising content/item viewing history and frequently patterns/habits of the target user/target profile – see include, but are not limited to, figures 2-3, col. 3, lines 8-20, col. 4, lines 15-30, col. 5, lines 10-45, col. 7,lines 23-42, col. 10, lines 10-12, col. 12,lines 15-25, lines 40-55, col. 14, line 55-col. 15, line 15, col. 16, lines 14-30) ;
generating a customized list of recommended content items for the target user, wherein the customized list of recommended content items is continuously updated (generating a list of recommended items with highest scored recommendations for target user/profile and the recommended items is continuously updated/modified based on change of the scores/interactions – see include, but are not limited to, figure 3, col. 10, lines 50-56, col. 14, lines 7-17, col. 16, lines 27-34); and
transmitting, by a communication module and over a communications networks, the customized list of recommended content items to a client device of the target user to play on the client device (transmitting, by a communication module of the server and over a communication between the server and the client, the recommended list of items targeted for the user to a client device (213) of the targeted user to display on the client device – see include, but are not limited to, figures 2-3, col. 14, lines 7-12, col. 17, lines 10-12).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Bovenschulte with the teaching of assigning a score to each content item and ranking the scored content item as taught by Sharma in order to yield predictable result of improving the user of data mining techniques in generating recommendations or effectively generating recommendations and improving chance for customer to accept the recommendation (col. 2, lines 35-45) or providing a best recommendations (col. 3, lines 14-15).
Regarding claim 3, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the collecting step is performed by a collector module collecting content utilization of an entire viewing community (collecting utilization data from all platforms by a collector module/audience measurement server – see include, but are not limited to, Bovenschulte: figure 1, paragraph 0012-0013, 0043).
Regarding claim 4, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the customized list of recommended content items comprises categories of interest to the target user (e.g., list of top programs comprises categories/genres of interest to the target user such as news, movies, etc. – see include, but are not limited to, Bovenschulte: paragraphs 0063, 0101-0102; Thomas: paragraph 0070; Berezowski: figures 10, 14).
Regarding claim 5, Bovenschulte in view of Sharma discloses the method of claim 2, wherein a recommended content item of the customized list is posted on a social networking application (the customized list/top items is posted or display on a social network application such as website or Internet application- see include, but are not limited to, Bovenschulte: figures 1,4, paragraphs 0070, 0099; Thomas: paragraphs 0058, figures 10a, 11; Berezowski: figures 2C-2E, paragraphs 0051, 0052; Sharma: figure 2, col. 5, lines 25-30, col. 6, lines 1-3) .
Regarding claim 6, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the content viewing history of the target user is determined by a social network of the target user (content viewing history of the target user is determined by a social network such as on line/Internet interactions/purchase of the user - see include, but are not limited to, Bovenschulte: figures 1,4, paragraphs 0043, 0051, 098-0099, 0117; Thomas: paragraphs 0058, figures 10a, 11; Berezowski: figures 2C-2E, paragraphs 0051, 0052; Sharma: figures 2-3, col. 5, lines 25-30, col. 6, lines 1-3) .
Regarding claim 7, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the generating step comprises generating the customized list of recommended content items for the target user further from stored data, media content data, and interactive applications (generating the list for target user from stored data of program, media content data such as video, television, and interactive application with links, website, etc. –see include, but are not limited to, Bovenschulte: figures 1,4, paragraphs 0039,0043, 0047-0051, 098-0099, 0101-0103, 0117; Thomas: paragraphs 0058, figures 10a-11; Berezowski: figures 8-10, 18-20; Sharma: figures 2-3).
Regarding claim 8, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the generating step comprises generating the customized list of recommended content items for the target user further from data provided by an application source (internet or content provider source, channel source – see include, but are not limited to, Bovenschulte: figures 1, 4, paragraphs 0033, 0039, 0101-0103).
Regarding claim 9, Bovenschulte in view of Sharma discloses the method of claim 8, wherein the application source is an interactive media application (see include, but are not limited to, Bovenschulte: figures 1, 4, paragraphs 0008-0009, 0042).
Regarding claim 10, Bovenschulte in view of Sharma discloses the method of claim 8, wherein the application source is a communication application (email, chat, internet communication application – see include, but are not limited to, Bovenschulte: figures 1, 4, paragraphs 0070, 0073).
Regarding claim 11, Bovenschulte in view of Sharma discloses the method of claim 8, wherein the application source is configured to execute on a mobile phone (see for example, Bovenschulte: paragraphs 0005, 0068,0098).
Regarding claim 12, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the recommended content items of the customized list of recommended content items is selected from a group consisting of: video, audio, Internet web pages, interactive games, broadcast programming, video on demand programs, local content, and targeted advertisements (see include, but are not limited to, Bovenschulte: figure 1, paragraphs 0101-0103; Berezowski: figures 8-16; Thomas: figures 7-11, paragraph 0070).
Regarding claim 13, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the content utilization data is collected from real time listeners provided at the plurality of client devices (real-time consumer/listener – see include, but are not limited to, Bovenschulte: figure 4, paragraphs 0035, 0063; Thomas: paragraphs 0009, 0057, 063; Berezowski: paragraphs 0069, 0074; Sharma: col. 6, lines 23-26).
Regarding claim 14, Bovenschulte in view of Sharma discloses the method of claim 13, wherein the content utilization data is collected from all the client devices (all platforms – see include, but are not limited to, Bovenschulte: figure 1, paragraph 0012-0013, 0043).
Regarding claim 15, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the profile data of the target user contains information collected from social connections of the target user (social connection such as via Internet, website, etc. - see include, but are not limited to, Bovenschulte: figures 1,4, paragraphs 0070, 0099; Thomas: paragraphs 0058, figures 10a, 11; Berezowski: figures 2C-2E, paragraphs 0051, 0052; Sharma: figure 2, col. 5, lines 25-30, col. 6, lines 1-3).
Regarding claim 16, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the content utilization data is collected from a viewing history of one or more social connections of the target user (see include, but are not limited to, Bovenschulte: figures 1,4, paragraphs 0043, 0051, 098-0099, 0117; Thomas: paragraphs 0058, figures 10a, 11; Berezowski: figures 2C-2E, paragraphs 0051, 0052; Sharma: figures 2-3, col. 5, lines 25-30, col. 6, lines 1-3).
Regarding claim 17, Bovenschulte in view of Sharma discloses the method of claim 2, further comprising assigning the different weights/scores to different types of content based on desired rules (see include, but are not limited to, Bovenschulte: paragraphs 0047-0053, 0092, 0119; Sharma: figures 2-3, col. 5, lines 1-7, col. 11, lines 1-10). Thus, it would have been obvious to one of ordinary skill in the art to incorporate that score by assigning a higher score for live content than other content in order to give real time higher priority than other content and allowing user to easily see the live content.
It is also noted that “live content” or “other content” are just types of data and are considered as non-functional descriptive material (see for example, Board decision in Ser. No. 10622876).
Regarding claim 18, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the customized list of recommended content is based on viewing habits of social connections of the target user (viewing habits/frequently pattern of user – see discussion in the rejection of claim 1; and see for example, Thomas: paragraphs 0055, 0062; Sharma: col. 1, lines 35-45, col. 4, lines 23-26); .
Regarding claim 19, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the profile data stored comprises the content viewing history, purchases, recording of content, and Internet content (interaction data comprises viewing history, purchase/order/buy items, recording of content, or browsing website, select a like to Internet source, etc. see include, but are not limited to, Bovenschulte: figures 10-14, paragraphs 0013, 0039, 0042; Sharma: figures 2-3).
Regarding claim 20, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the recommended content items comprise video (see include, but are not limited Bovenschulte: paragraphs 0101-0102; Berezowski: figures 8-10; Thomas: figures 10a, 11b, paragraph 0070).
Regarding claim 21, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the recommended content items comprise Internet web pages (see include, but are not limited Bovenschulte: paragraphs 0101-0102; Berezowski: figures 8-10; Thomas: figures 10a, 11b, paragraph 0070; Sharma: figures 2-3).
Regarding claim 22, Bovenschulte in view of Sharma discloses the method of claim 2, wherein the customized list of recommended content items transmitted to the client device of the target user to play on the client device comprises recommended contents items to display on the client device (see discussion in last limitation of claim 2 and see also include, but are not limited Bovenschulte: figures 1, 10, 14, paragraphs 0101-0102; Berezowski: figures 8-10; Thomas: figures 10a, 11b, paragraph 0070; Sharma: figures 2-3).
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 2-22 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-18 of U.S. Patent No. 9,699,503. Although the conflicting claims are not identical, they are not patentably distinct from each other because the instant claims 2-22 and Patent claims 1-18 are directed to the same invention with a different in scope and are therefore an obvious variant thereof or the invention defined in instant claims 2-22 is an obvious variation of the invention defined in the patent claims 1-18 because for limitations in the instant claims that are not recited in patent claims (e.g., viewing pattern…) are known by prior art (see for example, prior arts discussed in the rejection above). It would have been obvious to one of ordinary skill in the art combine in patent claims with the well-known teachings as taught in the prior art cited above for the benefit of improving efficiency of recommending content.
Allowance of claims 2-22 would result in an un-warranted timewise extension of the monopoly granted for the invention as defined in claims 1-18 of Patent No. 9,699,503.
Claims 2-22 are also rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 10,419,817. Although the conflicting claims are not identical, they are not patentably distinct from each other because the instant claims 2-22 and Patent claims 1-20 are directed to the same invention with a different in scope and are therefore an obvious variant thereof or the invention defined in instant claims 2-22 is an obvious variation of the invention defined in the patent claims 1-20 because for limitations in the instant claims that are not recited in patent claims (e.g., viewing pattern….) are known by prior art (see for example, prior arts discussed in the rejection above). It would have been obvious to one of ordinary skill in the art combine in patent claims with the well-known teachings as taught in the prior art cited above for the benefit of improving efficiency of recommending content.
Allowance of claims 2-22 would result in an un-warranted timewise extension of the monopoly granted for the invention as defined in claims 1-20 of Patent No. 10419817.
Claims 2-22 are also rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 11843827. Although the conflicting claims are not identical, they are not patentably distinct from each other because the instant claims 2-22 and Patent claims 1-20 are directed to the same invention with a different in scope and are therefore an obvious variant thereof or the invention defined in instant claims 2-22 is an obvious variation of the invention defined in the patent claims 1-20 because for limitations in the instant claims that are not recited in patent claims (e.g., viewing pattern….) are known by prior art (see for example, prior arts discussed in the rejection above). It would have been obvious to one of ordinary skill in the art combine in patent claims with the well-known teachings as taught in the prior art cited above for the benefit of improving efficiency of recommending content.
Allowance of claims 2-22 would result in an un-warranted timewise extension of the monopoly granted for the invention as defined in claims 1-20 of Patent No. 11843827.
Claims 2-22 are also rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-20 of U.S. Patent No. 12425687. Although the conflicting claims are not identical, they are not patentably distinct from each other because the instant claims 2-22 and Patent claims 1-27 are directed to the same invention with a different in scope and are therefore an obvious variant thereof or the invention defined in instant claims 2-22 is an obvious variation of the invention defined in the patent claims 1-27 because for limitations in the instant claims that are not recited in patent claims (e.g., by assigning score…) are known by prior art (see for example, prior arts discussed in the rejection above). It would have been obvious to one of ordinary skill in the art combine in patent claims with the well-known teachings as taught in the prior art cited above for the benefit of improving efficiency of recommending content.
Allowance of claims 2-22 would result in an un-warranted timewise extension of the monopoly granted for the invention as defined in claims 1-27 of Patent No. 12425687.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Linden et al. (US 201202159729) discloses discovery of behavior-based item relationship.
Dicker et al. (US 7720723) discloses user interface and method for recommending items to users.
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/AN SON P HUYNH/ Primary Examiner, Art Unit 3795
September 5, 2026
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