Prosecution Insights
Last updated: October 23, 2026
Application No. 18/629,815

ARTIFICIAL INTELLIGENCE SYSTEM FOR MEDIA ITEM CLASSIFICATION USING TRANSFER LEARNING AND ACTIVE LEARNING

Final Rejection §103
Filed
Apr 08, 2024
Priority
Jun 25, 2018 — continuation of 11/983,244
Examiner
WILLIAMS, JEFFERY A
Art Unit
2488
Tech Center
2400 — Computer Networks
Assignee
Amazon Technologies Inc.
OA Round
2 (Final)
84%
Grant Probability
Favorable
3-4
OA Rounds
0m
Est. Remaining
94%
With Interview

Examiner Intelligence

Grants 84% — above average
84%
Career Allowance Rate
788 granted / 941 resolved
+25.7% vs TC avg
Moderate +10% lift
Without
With
+10.4%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
49 currently pending
Career history
1022
Total Applications
across all art units

Statute-Specific Performance

§101
6.3%
-33.7% vs TC avg
§103
48.7%
+8.7% vs TC avg
§102
18.4%
-21.6% vs TC avg
§112
20.8%
-19.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 941 resolved cases

Office Action

§103
DETAILED ACTION The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Arguments Applicant’s arguments with respect to the obvious double patenting rejections of claims 21 and 26 have been fully considered and are persuasive. The obvious double patenting rejections of claims 21 and 26 have been withdrawn. Applicant’s arguments with respect to the 35 USC 103 rejections of claim(s) 21, 31, and 40 have been considered but are moot in view of the new grounds of rejection. 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. The factual inquiries 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. Claim(s) 21, 23, 31, 33, and 40 is/are rejected under 35 U.S.C. 103 as being unpatentable over MacLaurin (US 2007/0028171) in view of Herz et al. (Herz) (US Pat. No. 5,754,939). Regarding claims 21 and 31, MacLaurin discloses a system, comprising: one or more computing devices ([0228], a group of processors); wherein the one or more computing devices include instructions that upon execution on or across the one or more computing devices ([0228], a software program is executed): analyze consumer feedback pertaining to one or more media items of a catalog ([0025], a user input is detected for generating a set of proposed tags for items; [0029], a catalog such as an internet attorney list is used); generate, based at least in part on said analyzing, a set of proposed tags for other media items of the catalog, wherein individual proposed tags of the set of proposed tags represent respective classifications of media ([0025], [0026], a set of proposed tags is generated based on user input and associated with the current item and the tag may be associated on new data items not yet stored in item source 106; [0032], tag suggestions for a current item are generated based on tags previously used for similar items, a tag such as “HOUSE” is a classification of the item); and assign, to the other media items of the catalog, using one or more machine learning models, respective tags of the set of proposed tags ([0007], machine learning is applied for labeling items, [0025], [0026], a set of proposed tags is generated based on user input and associated with the current item and the tag may be associated on new data items not yet stored in item source 106, also recently utilized tags may be used for current items; [0025], tags for a new item are suggested based on tags of associated with previously tagged item; [0032], tag suggestions for a current item are generated based on tags previously used for similar items). MacLaurin is silent about subsequent to receiving consumer feedback from one or more consumers that pertains to one or more media items of a catalog previously accessed by the one or more consumers, analyzing the consumer feedback pertaining to the one or more media items; generating, based at least in part on said analyzing the consumer feedback pertaining to the one or more media items previously accessed by the one or more consumers, a set of proposed tags for other media items. Herz from the same or similar field of endeavor discloses subsequent to receiving consumer feedback from one or more consumers that pertains to one or more media items of a catalog previously accessed by the one or more consumers (col. 9, lns. 4-63, a catalog of objects including text, people, and cars is searched and the items are labeled; col. 22, lns. 42-46, a catalog of items), analyzing the consumer feedback pertaining to the one or more media items (col. 65, lns. 33-36, a user accessing a labeled cluster of items and navigating from the labelled cluster is analyzed); generating, based at least in part on said analyzing the consumer feedback pertaining to the one or more media items previously accessed by the one or more consumers, a set of proposed tags for other media items (col. 65, lns. 42-46, a user generated tag for a cluster of items is used globally for tagging all clusters containing the items; col. 65, lns. 47-58, a user supplied tag for Sports News cluster items in a catalog is used for automatically generating a “sports” tag for a cluster of items which were previously labeled International News based on a similarity metric of the clusters). 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 teachings of Herz into the teachings of MacLaurin for more accurate tagging of items. Regarding claims 23 and 33, MacLaurin discloses selecting, using a particular tag of the respective tags, a particular media item of the catalog for presentation to a media consumer (FIG. 7, [0044], items corresponding to tag data are presented). Regarding claim 40, MacLaurin discloses one or more non-transitory computer-accessible storage media storing program instructions that when executed on or across one or more processors ([0023], a program is executed by a processor): obtain, at a first user device, from a media consumer ([0025], a user device is used for requesting items), a request for presentation of one or more media items similar to a first media item of a catalog, wherein the request does not identify the one or more media items ([0025], a user starts typing and tag suggestions and items are provided for different items that may correspond to some of the typed characters (i.e. a specific item is not input)); identify, using at least a first tag which was (a) generated based at least in part on analysis of consumer feedback pertaining to one or more media items including the first media item and (b) assigned to the first media item, a second media item of the catalog for presentation in response to the request ([0007], machine learning is applied for labeling items, [0025], [0026], a set of proposed tags is generated based on user input and associated with the current item and the tag may be associated on new data items not yet stored in item source 106, also recently utilized tags may be used for current items; [0025], tags for a new item are suggested based on tags of associated with previously tagged item; [0032], tag suggestions for a current item are generated based on tags previously used for similar items); and cause the second media item to be presented via the first user device ([0035], tagged items are displayed to a user). MacLaurin is silent about identify, using at least a first tag which was (a) generated based at least in part on analysis of consumer feedback received from one or more consumers pertaining to one or more media items including the first media item that were previously accessed by the one or more consumers. Herz from the same or similar field of endeavor discloses identify(ing), using at least a first tag which was (a) generated based at least in part on analysis of consumer feedback received from one or more consumers pertaining to one or more media items including the first media item that were previously accessed by the one or more consumers (col. 65, lns. 42-46, a user generated tag for a cluster of items is used globally for tagging all clusters containing the items; col. 65, lns. 47-58, a user supplied tag for Sports News cluster items in a catalog is used for automatically generating a “sports” tag for a cluster of items which were previously labeled International News based on a similarity metric of the clusters). 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 teachings of Herz into the teachings of MacLaurin for more accurate tagging of items. Claim(s) 22, 25, 27, 32, 35, and 37 is/are rejected under 35 U.S.C. 103 as being unpatentable over MacLaurin (US 2007/0028171) in view of Herz et al. (Herz) (US Pat. No. 5,754,939), and further in view of Johnson et al. (Johnson) (US 2009/0012991). Regarding claims 22 and 32, MacLaurin in view of Herz discloses the system as recited in claim 31 (see claim 31 above). MacLaurin in view of Herz is silent about wherein the respective tags are assigned at a service of a cloud computing environment. Johnson from the same or similar field of endeavor discloses wherein the respective tags are assigned at a service of a cloud computing environment (FIG. 2, API servers and web interface (browser) servers are connected to a client device via cloud network 104; [0093], The Sell Your Item (SYI) user interface in a particular embodiment is intended for real-time user interaction via a web browser. The API interface is intended for programmatic access to the tag engine 500 via an application program). 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 teachings of Johnson into the teachings of MacLaurin in view of Herz for incorporating remote tagging services. Regarding claims 25 and 35, Johnson further discloses wherein the one or more computing devices include further instructions that upon execution on or across the one or more computing devices: in response to a programmatic request (FIG. 1, [0096], [0208], programmatic access to an API is performed) directed to a cloud computing environment (FIG. 2, API servers and web interface (browser) servers are connected to a client device via cloud network 104; [0093], The Sell Your Item (SYI) user interface in a particular embodiment is intended for real-time user interaction via a web browser. The API interface is intended for programmatic access to the tag engine 500 via an application program), train the one or more machine learning models, wherein the respective labels are assigned by trained versions of the one or more machine learning items ([0085], a Bayesian model is used for tagging items; [0090], training data is used to train a machine learning model for suggesting tags for items; [0091], a model is built for tagging items using training data). 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 teachings of Johnson into the teachings of MacLaurin for incorporating remote tagging services. Regarding claims 27 and 37, Johnson further discloses wherein the one or more machine learning models includes (e) a Bayesian model ([0085], a Bayesian model is used for tagging items). 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 teachings of Johnson into the teachings of MacLaurin for incorporating remote tagging services. Claim(s) 24 and 34 is/are rejected under 35 U.S.C. 103 as being unpatentable over MacLaurin (US 2007/0028171) in view of Herz et al. (Herz) (US Pat. No. 5,754,939), and further in view of Manning et al. (Manning) (US 2017/0140260). Regarding claims 24 and 34, MacLaurin in view of Herz discloses the system as recited in claim 31 (see claim 31 above). MacLaurin in view of Herz is silent about wherein the one or more computing devices include further instructions that upon execution on or across the one or more computing devices: select, using a particular tag of the respective tags, a particular media item for inclusion in a personalized playlist or personalized radio station of a client of a media service. Manning from the same or similar field of endeavor discloses wherein the one or more computing devices include further instructions that upon execution on or across the one or more computing devices: select, using a particular tag of the respective tags, a particular media item for inclusion in a personalized playlist of a client of a media service ([0045] media is added to a playlist based on a tag). 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 teachings of Manning into the teachings of MacLaurin in view of Herz for providing automatically personalized media selections to a user. Claim(s) 26, 28, 36, and 38 is/are rejected under 35 U.S.C. 103 as being unpatentable over MacLaurin (US 2007/0028171) in view of Herz et al. (Herz) (US Pat. No. 5,754,939), and further in view of Churchill et al. (Churchill) (US Pat. No. 8,521,679). Regarding claims 26 and 36, MacLaurin in view of Herz discloses the system as recited in claim 31 (see claim 31 above). MacLaurin in view of Herz is silent about wherein the other media items of the catalog comprise one or more of: (a) at least a portion of a music recording, (b) at least a portion of an audio recording of a book, a podcast, or a magazine article, (d) at least a portion of a video, or (e) at least a portion of a description of an item of a retail catalog. Churchill from the same or similar field of endeavor discloses wherein the other media items of the catalog comprise one or more of: (a) at least a portion of a music recording (col. 23, lns. 11-15, music data is tagged), (d) at least a portion of a video (col. 14, lns. 14-20, video data is used for tagging). 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 teachings of Churchill into the teachings of MacLaurin in view of Herz for incorporating tagging of audio and video items. Regarding claims 28 and 38, MacLaurin in view of Herz discloses the system as recited in claim 31 (see claim 31 above). MacLaurin in view of Herz is silent about wherein to analyze the consumer feedback, the one or more computing devices include further instructions that upon execution on or across the one or more computing devices: determine respective durations for which individual media items of the one or more media items were played or watched. Churchill from the same or similar field of endeavor discloses wherein to analyze the consumer feedback, the one or more computing devices include further instructions that upon execution on or across the one or more computing devices: determine respective durations for which individual media items of the one or more media items were played or watched (col. 2, lns. 26-35, the term “social activity” may refer to a user viewing media content; col. 16, lns. 12-14, the session duration of a social activity (i.e. a user viewing media content) is determined for tagging items; col. 3, lns. 49-55, tagging of media items is performed). 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 teachings of Churchill into the teachings of MacLaurin in view of Herz for accurate tagging of media items. Claim(s) 29 and 39 is/are rejected under 35 U.S.C. 103 as being unpatentable over MacLaurin (US 2007/0028171) in view of Herz et al. (Herz) (US Pat. No. 5,754,939), and further in view of Galuten et al. (Galuten) (US 2016/0071058). Regarding claims 29 and 39, MacLaurin in view of Herz discloses the computer-implemented method as recited in claim 21 (see claim 21 above) and a set of proposed tags (See claim 31 above). MacLaurin in view of Herz is silent about wherein a particular tag indicates a geographical region in which at least a particular media item is popular. Galuten from the same or similar field of endeavor discloses wherein a particular tag of indicates a geographical region in which at least a particular media item is popular ([0107], tags are added to a media item based on viewer location and how much was each video viewed (e.g., did many people stop after 1 minute, how many people watched it multiple times, what part of the video was watched most often)). 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 teachings of Galuten into the teachings of MacLaurin in view of Herz for accurate tagging of media items. Claim(s) 30 is/are rejected under 35 U.S.C. 103 as being unpatentable over MacLaurin (US 2007/0028171) in view of Herz et al. (Herz) (US Pat. No. 5,754,939), and further in view of Hein et al. (Hein) (US 2013/0297638). Regarding claim 30, MacLaurin in view of Herz discloses the computer-implemented method as recited in claim 21 (see claim 21 above) and a set of proposed tags (See claim 31 above). MacLaurin in view of Herz is silent about wherein a particular tag of the set of proposed tags indicates an age group of media consumers among which at least a particular media item is popular. Hein from the same or similar field of endeavor discloses wherein a particular tag indicates an age group of media consumers among which at least a particular media item is popular. ([0059], tags are added to a media item based on an age group that watches the video the most). 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 teachings of Hein into the teachings of MacLaurin in view of Herz for accurate tagging of media items. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Barnett et al. (Barnett) (US 2018/0181844) ([0040], auto tagging of items is performed). Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to JEFFERY A WILLIAMS whose telephone number is (571)270-7579. The examiner can normally be reached M-F 8:00-5:00. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sath Perungavoor can be reached at 571-272-7455. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JEFFERY A WILLIAMS/ Primary Examiner, Art Unit 2488
Read full office action

Prosecution Timeline

Apr 08, 2024
Application Filed
May 12, 2026
Non-Final Rejection mailed — §103
Aug 11, 2026
Response Filed
Oct 16, 2026
Final Rejection mailed — §103 (current)

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Prosecution Projections

3-4
Expected OA Rounds
84%
Grant Probability
94%
With Interview (+10.4%)
2y 7m (~0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 941 resolved cases by this examiner. Grant probability derived from career allowance rate.

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