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 Objections
Claim 4 is objected to because of the following informalities: Claim 4 reads wherein the user-dependent weightings are based on at least one of: at least one of: … . This appears to be a typographical error, repeating the phrase at least one of: and the claim will be interpreted as if the phrase at least one of: had only appeared once. Appropriate correction is required.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim 1 recites a method, thus a process, one of the four statutory categories of patentable subject matter. However, the claim further recites the steps of selecting a set of audio clips (a mental process); calculating one or more user-independent weightings for each clip in the set (a mental process); calculating one or more user-dependent weightings for each clip in the set (a mental process); combining the suer independent and dependent weightings into an overall weighing for each clip, for a user, to generate an overall weighted set of audio clips (a mental process); selecting at least two of the overall weighted set of audio clips to obtain a candidate set (a mental process); and applying a set of rules to the candidate set to obtain a tracklist of audio clips (a mental process) to be played to the user in each of one or more subsequent timeslots (an intended use, which is given negligible patentable weight). Thus, the claim recites only mental process steps, and is thus directed to an abstract idea (a set of decisions to determine a tracklist), without significantly more.
Claims 2-6, 12, and 13, each dependent upon Claim 1, recite additional elements which merely limit the data being processes via the mental process, e.g. specifying the field of use of the abstract idea, which by MPEP 2106.05(h) cannot integrate the abstract idea into a practical application nor provide significantly more than the abstract idea itself.
Claims 7, 11, and 14-18, further dependent upon Claim 1, recite either additional mental process steps (e.g. two tracklists are generated and combined; setting the weight of each audio clip to include the weight of all rules; selecting songs at random; selecting a top 10% weighted songs) or recite specifics of how previously recited mental steps are performed (to recursively apply rules; set the weight of a clip to zero if a rule is violated; some rules are not applied based on weightings) but recite no additional elements, thus cannot recite any additional elements which could integrate the abstract idea into a practical application nor provide significantly more than the abstract idea itself.
Claim 8, dependent upon Claim 1, recites insignificant extra-solution activity of outputting data computed in the mental process steps (offering to the user audio clips), which by MPEP 2106.05(g) cannot integrate the abstract idea into a practical application, and which by MPEP 2106.05(d) is well-understood, routine, and conventional (presenting offers) and thus cannot provide an inventive concept. Claims 9 and 10, dependent upon Claim 8, recite either additional mental process steps (e.g. affinity is calculated) or recite specifics of how previously recited mental steps are performed (affinity is one of a number of types) but recite no additional elements, thus cannot recite any additional elements which could integrate the abstract idea into a practical application nor provide significantly more than the abstract idea itself.
Claim 19 recites a system, comprising at least one processor; a display; and memory containing instructions to perform precisely the method of Claim 1. As performance of an abstract idea on generic computer components can neither integrate the abstract idea into a practical application nor provide significantly more than the abstract idea itself, Claim 19 is rejected for reasons set forth in the rejection of Claim 1.
Claim 20, dependent upon Claim 19, only recites additional elements which merely limit the data being processes via the mental process, e.g. specifying the field of use of the abstract idea, which by MPEP 2106.05(h) cannot integrate the abstract idea into a practical application nor provide significantly more than the abstract idea itself.
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 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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-6, 17, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Hicken, US PG Pub 2009/0228423, in view of Celma, “Music Recommendation and Discovery.”
Regarding Claim 1, Hicken teaches a method of creating a sequence of audio clips to be played to a user (Abstract, “a music recommendation system … generates a playlist of songs”), comprising: selecting a set of audio clips ([0011], “musical pieces owned by a consumer ... each musical piece in the consumer’s library is addressed” & [0012], “in summary, the attributes at the selected external locations are treated as though they are an extension of the internal data base” denote that clips on the user device, as well as clips not on the user device, are selected for analysis) … calculating one or more user-dependent weightings for each clip in the set (Abstract, “a music recommendation system receives a user selection of desired music” where, Fig. 8A, the selection may be a song (element 300), user selection denotes user-dependent, and (elements 306 & 316) “Distance Calculations” are performed for “Processed Audio Pieces”/clips (element 312), where a calculated distance from a user-selected song denotes a user dependent weighting) … selecting at least two of the overall weighted set of audio clips to obtain a candidate set (Fig. 8A, element 312, “Return X Number of Processed Audio Pieces Within Threshold Distance” where the context of [0097], “returns all or a portion of the processed audio pieces” indicates that X can be at least two); and applying a set of rules to the candidate set to obtain a tracklist of audio clips to be played to the user in each of one or more subsequent timeslots ([0098], “further selects as many audio pieces from the identified set of audio pieces that would satisfy the desired playlist size. the audio pieces selected from the identified set may also depend on the setting of the variety sliding bar” where “desired playlist size” denotes one or more subsequent timeslots and “setting of the variety sliding bar” denotes one rule; further, Abstract, “user-selectable shuffling mechanisms are provide to allow the order of the songs to be shuffled” denotes a second rule to obtain a tracklist).
Hicken does not teach, but Celma does teach, calculating one or more user-independent weightings for each clip (Celma, pg. 6, 1st paragraph, “recommender systems should exploit the long tail of popularity (e.g. number of total plays, or album sales)” & pg. 37, last paragraph, “the timestamp of an item (e.g. when the item was added to the collection) is an important factor for the recommendation algorithm. The prediction function can take into account the age of an item” & pg. 139, 3rd paragraph, “we add now the popularity factor (measured with the total playcounts per artist)” denotes one user-independent weighting) and combining the user independent and user dependent weightings into an overall weighting for each clip, for a user, to generate an overall weighted set of audio clips (Celma, pg. 35, 2nd paragraph, “Weighted. A hybrid method that combines the outputs of separate approaches using, for instance, a linear combination of the scores of each recommendation technique” denotes that different scores/weightings from different kinds of recommenders can be combined).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate and combine the user-independent factors of Celma into the music recommendation system of Hicken because both inventions concern recommending audio clips to users. The motivation to do so is “to allow users to discover new music” … “Effective recommendation systems should promote novel and relevant material (non-obvious recommendations) taken primarily from the tail of a distribution, rather than focus on accuracy” (Celma, pg. 6, 1st and 2nd paragraphs).
Regarding Claim 2, the Hicken/Celma combination of Claim 1 teaches the method of Claim 1 (and thus the rejection of Claim 1 is incorporated). The combination has been shown to teach, via Celma, user independent weightings based on at least one of … song popularity distribution (Celma, pg. 35, 2nd paragraph, “the scores of each recommendation technique” denotes weightings with pg. 6, 1st paragraph, “recommender systems should exploit the long tail of popularity (e.g. number of total plays, or album sales)” & pg. 37, last paragraph, “the timestamp of an item (e.g. when the item was added to the collection) is an important factor for the recommendation algorithm. The prediction function can take into account the age of an item” & pg. 155, last paragraph, “The temporal effects in the Long Tail are another aspect one should take into account. Some new artists can be very popular, gather a spike of attention when they release an album, but they can slowly move towards the mid or tail area of the curve as time goes by”).
Regarding Claim 3, the Hicken/Celma combination of Claim 1 teaches the method of Claim 1 (and thus the rejection of Claim 1 is incorporated). Hicken further teaches wherein the user dependent weightings are based on user preferences ([0005], “method of recommending items to a person which are based on the user’s preferences”). Hicken does not explicitly teach recommendations based on user listening history, but Celma teaches this limitation (Celma, pg. 18, 2nd paragraph, “There are several approaches to represent user preferences. For instance, using … the listening habits (songs that a user listens to)”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate user listening history into the calculation to determine the weights in the Hicken/Celma combination. The motivation to do so is that “listening habits” give insight into “user preferences” (Celma, pg. 18, 2nd paragraph).
Regarding Claim 4, the Hicken/Celma combination of Claim 1 teaches the method of Claim 1 (and thus the rejection of Claim 1 is incorporated). Hicken further teaches wherein the user-dependent weightings are based on at least one of: … presets (Hicken, Abstract, “receives a user selection of desired music … and generates a playlist of songs based on the analysis data” & [0113], “the starting anchor point may be preset by a user … if the user sets the anchor point as a particular artist [the system] plays songs associated with the artist”) … mood ([0105], “if the playlist is to be based on … a mood group”).
Regarding Claim 5, the Hicken/Celma combination of Claim 1 teaches the method of Claim 1 (and thus the rejection of Claim 1 is incorporated). Hicken further teaches rules including one or more of: ... sequence_quota ([0082], “the size of the playlist may be customizable based on a number of tracks”), shuffle ([0075], “the processor provides four different types of shuffling mechanisms … the user may decide which shuffling mechanism will be associated”) … and time_quota ([0082], “the size of the playlist may be customizable based on … playing time”).
Regarding Claim 6, the Hicken/Celma combination of Claim 1 teaches the method of Claim 1 (and thus the rejection of Claim 1 is incorporated). Hicken further teaches wherein the one or more subsequent timeslots is any integer between 5 and 100 ([0099], “thus, if six audio pieces are to be recommended on the playlist”).
Regarding Claim 17, the Hicken/Celma combination of Claim 6 teaches the method of Claim 6 (and thus the rejection of Claim 6 is incorporated). Hicken further teaches wherein selecting audio clips to obtain a candidate set includes one or more of: … (ii) selecting all the songs in the overall weighted set; and (iii) selecting those songs in the overall weighted set above some defined threshold ([0097], “the recommendation engine returns all or a portion of the processed audio pieces as the recommended pieces for the playlist. In this regard, the recommendation engine may identify audio pieces whose total vector distance is below a threshold distance” where “below a threshold distance” denotes above some defined threshold closeness).
Regarding Claim 19, Hicken teaches a system, comprising: at least one processor ([0008], “the end user device also includes a processor executing instructions”), a display ([0044], “the data output device may include a computer display screen”), and memory containing instructions that, when executed, cause the at least one processor to ([0048], “the memory stores computer program instructions include the various engines”): select a set of audio clips ([0011], “musical pieces owned by a consumer ... each musical piece in the consumer’s library is addressed” & [0012], “in summary, the attributes at the selected external locations are treated as though they are an extension of the internal data base” denote that clips on the user device, as well as clips not on the user device, are selected for analysis) … calculate one or more user-dependent weightings for each clip in the set (Abstract, “a music recommendation system receives a user selection of desired music” where, Fig. 8A, the selection may be a song (element 300), user selection denotes user-dependent, and (elements 306 & 316) “Distance Calculations” are performed for “Processed Audio Pieces”/clips (element 312), where a calculated distance from a user-selected song denotes a user dependent weighting) … select at least two of the overall weighted set of audio clips to obtain a candidate set (Fig. 8A, element 312, “Return X Number of Processed Audio Pieces Within Threshold Distance” where the context of [0097], “returns all or a portion of the processed audio pieces” indicates that X can be at least two); and apply a set of rules to the candidate set to obtain a tracklist of audio clips to be played to the user in each of one or more subsequent timeslots ([0098], “further selects as many audio pieces from the identified set of audio pieces that would satisfy the desired playlist size. the audio pieces selected from the identified set may also depend on the setting of the variety sliding bar” where “desired playlist size” denotes one or more subsequent timeslots and “setting of the variety sliding bar” denotes one rule; further, Abstract, “user-selectable shuffling mechanisms are provide to allow the order of the songs to be shuffled” denotes a second rule to obtain a tracklist).
Hicken does not teach, but Celma does teach, to calculate one or more user-independent weightings for each clip (Celma, pg. 6, 1st paragraph, “recommender systems should exploit the long tail of popularity (e.g. number of total plays, or album sales)” & pg. 37, last paragraph, “the timestamp of an item (e.g. when the item was added to the collection) is an important factor for the recommendation algorithm. The prediction function can take into account the age of an item” & pg. 139, 3rd paragraph, “we add now the popularity factor (measured with the total playcounts per artist)” denotes one user-independent weighting) and combining the user independent and user dependent weightings into an overall weighting for each clip, for a user, to generate an overall weighted set of audio clips (Celma, pg. 35, 2nd paragraph, “Weighted. A hybrid method that combines the outputs of separate approaches using, for instance, a linear combination of the scores of each recommendation technique” denotes that different scores/weightings from different kinds of recommenders can be combined).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate and combine the user-independent factors of Celma into the music recommendation system of Hicken because both inventions concern recommending audio clips to users. The motivation to do so is “to allow users to discover new music” … “Effective recommendation systems should promote novel and relevant material (non-obvious recommendations) taken primarily from the tail of a distribution, rather than focus on accuracy” (Celma, pg. 6, 1st and 2nd paragraphs).
Regarding Claim 20, the Hicken/Celma combination of Claim 19 teaches the system of Claim 19 (and thus the rejection of Claim 19 is incorporated). Hicken further teaches wherein the user dependent weightings are based on at least one of: user preferences ([0005], “method of recommending items to a person which are based on the user’s preferences”) ... presets (Hicken, Abstract, “receives a user selection of desired music … and generates a playlist of songs based on the analysis data” & [0113], “the starting anchor point may be preset by a user … if the user sets the anchor point as a particular artist [the system] plays songs associated with the artist”) …[and] mood ([0105], “if the playlist is to be based on … a mood group”). Hicken does not teach user-independent weightings, but as demonstrated in the rejection of Claim 19, Celma teaches user independent weightings based on at least one of … song popularity distribution (Celma, pg. 35, 2nd paragraph, “the scores of each recommendation technique” denotes weightings with pg. 6, 1st paragraph, “recommender systems should exploit the long tail of popularity (e.g. number of total plays, or album sales)” & pg. 37, last paragraph, “the timestamp of an item (e.g. when the item was added to the collection) is an important factor for the recommendation algorithm. The prediction function can take into account the age of an item” & pg. 155, last paragraph, “The temporal effects in the Long Tail are another aspect one should take into account. Some new artists can be very popular, gather a spike of attention when they release an album, but they can slowly move towards the mid or tail area of the curve as time goes by”).
Claims 7, 13, 15, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Hicken, in view of Celma, and further in view of Plastina et al., US PG Pub 2006/0218187.
Regarding Claim 7, the Hicken/Celma combination of Claim 1 teaches the method of Claim 1 (and thus the rejection of Claim 1 is incorporated). Hicken does not explicitly teach, but Plastina teaches, a set of rules recursively applied to the candidate set for each timeslot (Plastina, Fig. 2, each filter is a rule, recursively applied one after another to the set of possible audio clips) and if there are insufficient audio clips in the candidate set to generate an audio clip for the given timeslot, then more of more of the rules may be at least one of: (i) allowed to be violated in whole or in part (Plastina, pg. 8, where ordering filters are rules, “FollowWithNextTrackOnAlbum” is a rule that may be violated when the candidate set doesn’t include sufficient audio clips on the same album: “Offers a steep preference to the other tracks on the same album (when present) in track order (when possible)”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the ordering rule exceptions of Plastina in the invention of Hicken because both inventions concern rules for creating and ordering playlists. The motivation to do so is to allow “the size of the playlist [to be] customizable based on a number of tracks, playing time, or buffer size” (Hicken, [0082]).
Regarding Claim 13, the Hicken/Celma combination of Claim 1 teaches the method of Claim 1 (and thus the rejection of Claim 1 is incorporated). Hicken does not teach, but Plastina does teach, wherein each rule has a weighting ([0030], “Each of the filters of the user-associated ordering filter is assigned a weight” where an “ordering filter” denotes a rule to obtain a tracklist). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include the ordering rule exceptions of Plastina in the invention of Hicken because both inventions concern rules for creating and ordering playlists. The motivation to do so is that “controlling filter weighting is generally effective for enhancing the importance of particular filters over others” (Plastina, [0041]).
Regarding Claim 15, the Hicken/Celma/Plastina combination of Claim 13 teaches the method of Claim 13 (and thus the rejection of Claim 13 is incorporated). Hicken does not teach wherein rules are not applied based on their weightings, wherein rules with lower weightings are allow to be violated prior to rules with higher weightings, but Plastina teaches this limitation (Plastina, [0029], “Each of the filters 79 is assigned a weight, whereby each filter impacts the filtering of the media items according to its relative weight … The null filter has no affect on the weighting and allows all media items to pass through” see table in [0035]).
Regarding Claim 16, the Hicken/Celma/Plastina combination of Claim 13 teaches the method of Claim 13 (and thus the rejection of Claim 13 is incorporated). Hicken does not teach initially setting the weight of each audio clip to include the weight of all rules, and if a rule is broken by an audio clip, subtracting the weight of that rule from the weight of the audio clip. However, Plastina teaches summing the weights of all rules to determine a maximum score for an audio clip (Platina, pg. 5, the Table just above [0039] has a “Maximum Possible Score”). Plastina then teaching summing the weight of each rule that is fulfilled by a particular audio clip. Subtracting the score of a rule that is broken from a maximum possible score is obvious in view of Plastina, because the act of subtracting from a maximum the scores of broken rules, consists of a “simple substitution of one known element for another to obtain predictable results” from the act of adding from zero the scores of un-broken rules, to approach the same maximum (as does Plastina, [0039], “these scores are then weighted and added together”), as per the KSR Rationales. 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 ordering rule exceptions calculations, that are obvious over Plastina into the invention of Hicken because both inventions concern rules for creating and ordering playlists. The motivation to do so is that “controlling filter weighting is generally effective for enhancing the importance of particular filters over others” (Plastina, [0041]).
Claims 8-10 are rejected under 35 U.S.C. 103 as being unpatentable over Hicken, in view of Celma, and further in view of Qureshi, US Patent 9,383,965.
Regarding Claim 8, the Hicken/Celma combination of Claim 1 teaches the method of Claim 1 (and thus the rejection of Claim 1 is incorporated). Hicken further teaches in addition to the tracklist, offering to the user audio clips for play ([0071], “selection of the e-commerce icon causes the downloaded e-commerce engine to search across one or more distinct databases of one or more providers for recommendations of songs, albums, and/or the like, similar to a selected audio piece, album, or artist. The songs and/or albums recommended as a result of searching the provider database are then displayed” denotes offering audio clips for play). Hicken does not teach that these clips have an affinity for a set of most recent audio clips that were played, but Qureshi teaches that “based on recently played music, a recommendation for additional music may be generated” (Qureshi, column 3, line 3). It would have been obvious to one of ordinary skill in the art to offer audio clips for purpose, as does Hicken, based on recently played music, as the recommendations of Qureshi, because both inventions concern making music recommendations. The motivation to do so is to “leverage the tendency to listen to music in phases” (Qureshi, column 2, lines 2-3).
Regarding Claim 9, the Hicken/Celma/Qureshi combination of Claim 8 teaches the method of Claim 8 (and thus the rejection of Claim 8 is incorporated). The combination, via Qureshi, further teaches wherein the affinity is at least one of (i) channel to channel (Qureshi, column 3, lines 5-10, “the library analyzer determines a relationship between Album A & Album B. If, at a later point in time, the user reverts back to his or her behavior of listening to music from Album A or music similar to Album A, then the library analyzer may generate a recommendation for music from Album B or music similar to Album B”) … (v) artist to song (Qureshi, column 2, lines 60-65, “plays back music of a particular genre, artist, or band … revisiting his or her interest in that band’s music at a later point in time”).
Regarding Claim 10, the Hicken/Celma/Qureshi combination of Claim 9 teaches the method of Claim 9 (and thus the rejection of Claim 9 is incorporated). The combination, via Qureshi, further teaches wherein the affinity is calculated based on frequency counts of said most recent songs played (Qureshi, column 2, lines 56-64, “The behavioral pattern of listening to at album at a high playback frequency for a substation duration of time may be tracked and used to generate a recommendation”).
Claims 11 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Hicken, in view of Celma, and further in view of Korteweg, US PG Pub 2013/0305385.
Regarding Claim 11, the Hicken/Celma combination of Claim 1 teaches the method of Claim 1 (and thus the rejection of Claim 1 is incorporated). Hicken does not explicitly teach, but Korteweg does teach, wherein a tracklist is generated for each of two or more genres of audio content (Korteweg, [0020], “having the service generate one or more playlists of media files; i.e. subsets of the entire database in which the subsets share one or more parameters, such as music genre”), and the tracklists are then combined in a mashup to generate a mixed audio content output (Korteweg, [0045], “Playlists may also be a combination of one or more other existing playlists” & [0051], “to create custom mashup playlist stations which combine other existing playlists”). It would have been obvious to one of ordinary skill in the art to incorporate the mashup features of Korteweg into the recommendation system of Hicken because both inventions provide music playlists. The motivation to do so is to allow “for instance, promotional messages intended to sell a product” (Korteweg, [0042]).
Regarding Claim 12, the Hicken/Celma combination of Claim 11 teaches the method of Claim 11 (and thus the rejection of Claim 11 is incorporated). Hicken does not teach, but Kortweg further teaches wherein the genres of audio content include any of talk, [and] music (Korteweg, [0042], “a service is provided to generate a playlist of music tracks with custom messages inserted between or during songs” where “custom messages” denotes talk). It would have been obvious to one of ordinary skill in the art to incorporate the mashup features of Korteweg into the recommendation system of Hicken because both inventions provide music playlists. The motivation to do so is to allow “for instance, promotional messages intended to sell a product” (Korteweg, [0042]).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Hicken, in view of Celma, and further in view of Dykstra, US Patent 8,554,640.
Regarding Claim 18, the Hicken/Celma combination of Claim 6 teaches the method of Claim 6 (and thus the rejection of Claim 6 is incorporated). Hicken does not explicitly teach selecting the top 10% weighted songs in the overall weighted set but Dykstra, also in the art of content recommendation, does teach this proportion of media items to select (Dykstra, column 18, lines 54-57, “a recommendation of a top k ranked content items is generated … For example, the top ten ranked items may be provided, or the top ten percent of ranked items”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to only deal with the top ten percent of songs, as does Dkykstra, in the Hicken/Celma invention. The motivation to do so is to make sure only to provide highly-ranked items to the user.
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 § 2146 et seq. 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 1-4 , 8-14, and 19 are rejected on the ground of nonstatutory double patenting as being unpatentable over Claims 1, 2, 3, 3, 4, 4, 4, 5, 5, 1, 1, and 1, respectively, of U.S. Patent No. 11,210,338. Although the claims at issue are not identical, the reference claims anticipate the corresponding instant claims.
Claims 1-4 and 8-14 are rejected on the ground of nonstatutory double patenting as being unpatentable over Claims 1, 2, 3, 3, 4, 4, 4, 5, 5, 1, and 1, respectively, of U.S. Patent No. 11,921,778. Although the claims at issue are not identical, the reference claims anticipate the corresponding instant claims.
Conclusion
Claim 14 has been searched, but no combination of prior art which renders the claim obvious has been uncovered. However, the claim remains rejected under 35 U.S.C. 101 as directed towards an abstract idea without significantly more, and as obvious-type double patenting.
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure: Paus, US PG Pub 2006/0200449, teaches other strategies for selecting media content based on a set of rules or filters including weights.
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/BRIAN M SMITH/ Primary Examiner, Art Unit 2122
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