Prosecution Insights
Last updated: April 19, 2026
Application No. 18/516,730

DIGITAL AVATAR RECOMMENDATION METHOD AND RECOMMENDATION SYSTEM

Non-Final OA §102§103
Filed
Nov 21, 2023
Examiner
GART, MATTHEW S
Art Unit
3696
Tech Center
3600 — Transportation & Electronic Commerce
Assignee
Alibaba (China) Co., Ltd.
OA Round
3 (Non-Final)
9%
Grant Probability
At Risk
3-4
OA Rounds
2y 5m
To Grant
26%
With Interview

Examiner Intelligence

Grants only 9% of cases
9%
Career Allow Rate
6 granted / 65 resolved
-42.8% vs TC avg
Strong +17% interview lift
Without
With
+17.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 5m
Avg Prosecution
9 currently pending
Career history
74
Total Applications
across all art units

Statute-Specific Performance

§101
40.5%
+0.5% vs TC avg
§103
32.3%
-7.7% vs TC avg
§102
10.1%
-29.9% vs TC avg
§112
13.2%
-26.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 65 resolved cases

Office Action

§102 §103
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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 1/14/2026 has been entered. Priority This application claims the following priority: FOREIGN APPLICATIONS CHINA CN202211489297.3 11/25/2022 IDS The following IDS(s) have been considered by the Examiner: None Examiner Note Claims 9 and 17 are cancelled by applicant. Claims 1, 12, and 20 have been amended by applicant Claims 1-8, 10-16, and 18-22 are pending in the instant application. Claims 1-8, 10-16, and 18-22 are rejected as set forth below. Response to Arguments The applicant incorrectly states that claims 1, 5-7, 11-16, and 19-20 are rejected under 35 USC 102(a)(1) over Brazell in view of Samsung. On page 4 of the previous office action, the rejection was under the 35 USC 103 heading and appropriately formulated in view of Graham v. John Deere Co. | 383 U.S. 1 (1966). There was a typographical error in the heading which has been corrected. The Examiner apologies for any confusion. The applicant notes that in the Office Action, the Office does not give any reason or theories on why and how claims 8 and 18 are rejected. The Examiner notes, claim 8 was rejected under 35 U.S.C. 103 as being unpatentable over Brazell (US 2014/0136361) in view of Samsung (WO 2021/125843 A1) in further view of Brannan (US2024/0087038). This rejection was presented to applicant on page 10 and page 11 of the previous office action. The Examiner notes, claim 18 was rejected under 35 U.S.C. 103 as being unpatentable over Brazell US2014/0136361 A1 in view of Samsung (WO 2021/125843 A1). The Examiner commented on claim 18 on page 17 of the previous office action. The applicant argues that Samsung does not discuss the “…lines between nodes 1116” in Fig. 11. The Examiner notes, the K-NN graph comprises a plurality of sets 1114 of nodes 1116. In particular embodiments, each set 1114 of nodes 1116 may correspond to a semantic context. As an example and not by way of limitation, each set 1114 may be shown by the dotted circles/ovals. In particular embodiments, each node 1116 may correspond to a particular semantic context and include one or more expressions, behaviors, actions associated with the node 1116. The lines as shown in Fig. 11 illustrates that correspondence (i.e., linking as claimed). 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action. 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) 1, 5-7, 10-16, and 18-22 are rejected under 35 U.S.C. 103 as being unpatentable over Brazell US2014/0136361 A1 in view of Samsung (WO 2021/125843 A1). Referring to claim 1, Brazell discloses a recommendation method, comprising: obtaining current state data, by a digital avatar recommendation system, the current state data including user information of a target user ([0016] “An avatar acts as a digital representation of a user by continually searching for information and analyzing the information to provide quantified measurements of the utility of decisions the user may make.”), scenario information of a current scenario, and history information of an interaction between the target user and the digital avatar, the digital avatar recommendation system including a computer-simulated digital avatar and an agent in the digital avatar (Brazell [0032] Avatar 202 can be configured to continually learn about user 201. For example, avatar 202 can obtain information about medical, educational, financial, and preference characteristics of user 201. Medical characteristics can include user 201's genetic information, health history, current well-being, etc. … Preference characteristics can include any other information about user 201 such as activities the user enjoys, habits, previous interaction that user 201 has had with avatar 202, etc. In short, avatar 202 can learn any type of information about user 201 thereby allowing avatar 202 to most effectively function as a digital representative of user 201.); mapping, by the agent in the digital avatar, the current state data to a target action in a candidate action set based on a current policy obtained through reinforcement learning, a candidate action in the candidate action set corresponding to a to-be-recommended content category, and the target action corresponding to a target content category (Brazell [0051] “In summary, avatar 202 constantly learns about user 201 and about any available information that is relevant to user 201's wellbeing.”); and performing, by the digital avatar, a target interaction with the target user, wherein the target interaction is used to recommend the target content category (Brazell Fig. 4). Brazell does not disclose, but Samsung discloses wherein the user information includes graph data of a relationship network graph of the target user, the relationship network graph including a node representing the target user and an edge linked to the node (Samsung Fig. 11) and representing an association relationship involving the target user (Samsung Fig. 12), and wherein the mapping the current state to the target action includes mapping the current state data to the target action based on the relationship network graph of the target user (Samsung Fig. 12). This noted feature in Samsung is applicable to the method of Brazell as both prior art references share characteristics and capabilities, namely, they are generally related to virtual environments. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Brazell as described above in order to provide a life like human user experience (Samsung page 6). The Examiner notes, reinforcement learning is a machine learning technique that trains software to make desired choices by rewarding good behavior and penalizing bad ones, the is taught by Brazell wherein Brazell uses scores to identify the trustworthiness of users (Brazell [0051]). Referring to claim 5, Brazell discloses a method according to claim 1, further comprising: obtaining a target feedback of the target user for the target interaction; determining, based on the target feedback, a reward score corresponding to the target action; and updating the current policy based on the reward score (Brazell Abstract, “A score representing how often the user follows the avatar's decisions can be maintained as an indication of the trustworthiness of the user in entering into personal decision contracts.”). Referring to claim 6, Brazell discloses a method according to claim 5, wherein the determining the reward score corresponding to the target action including: determining that the reward score is a first value in response to the target feedback indicates that the target user accepts the target content category; and determining that the reward score is a second value in response to the target feedback indicates that the target user does not accept the target content category, where the second value is less than the first value (Brazell [0050] … In other words, the score can also be viewed as a representation of how much trust user 201 has in avatar 202.). Referring to claim 7, Brazell discloses the method according to claim 1, wherein the mapping the state data to the target action in the candidate action set includes: determining, based on the state data, long-term cumulative reward Q values corresponding to candidate actions in the candidate action set; and determining the target action based on the long-term cumulative reward Q values (Brazell [0051] “… User 201's trust in avatar 202 can be quantified and used as a score in a marketplace where other entities or users can enter into personal decision contracts with user 201. These personal decision contracts are commitments to follow decisions made by avatar 202.”). Referring to claim 10, Brazell does not disclose wherein the current state data further includes graph data of a knowledge graph, and an entity in the knowledge graph corresponds to the to-be-recommended content category. Samsung discloses this (Samsung page 10-page 11, “In particular embodiments, the one or more computing systems for generating a digital avatar may provide an interface to a knowledge graph engine, question answering engine, or any form of a digital assistant through the digital avatar...”). Referring to claim 11, Brazell discloses the method according to claim 1, wherein the digital avatar has configuration parameters defining character features of the digital avatar, and the state data further includes the configuration parameters (Brazell [0036] “In some embodiments, avatar 202 can also be configured to identify how user 201 is spending time or money on other decisions and can make recommendations to reallocate the time or money…”). Referring to claims 12-16 and 18-22, the claims are rejected under the same rationale as set forth above. 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. Claim(s) 2-4, 8 are rejected under 35 U.S.C. 103 as being unpatentable over Brazell (US 2014/0136361) in view of Samsung (WO 2021/125843 A1) in further view of Brannan (US2024/0087038) Referring to claim 2, Brazell in view of Samsung does not disclose a method wherein the current scenario is a live streaming scenario, the digital avatar is a live streamer in the live streaming scenario, and the target user is a user entering the live streaming scenario. Brannon discloses this. ([0041] “For example, FIG. 2 illustrates an example of virtual character 210 in virtual environment 200 standing at a virtual kiosk 220 with a virtual salesperson 230 standing within the virtual kiosk 220.”). This noted feature in Brannon is applicable to the method of Brazell in view of Samsung as the prior art references share characteristics and capabilities, namely, they are generally related to virtual environments. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Brazell in view of Samsung as described above because many virtual environments do not provide adequate security for particular types of transactions, and/or do not adequately determine which types of transactions should receive additional security (Brannon [0003]). The Examiner notes, Samsung does disclose the use of real-time responses and broadcasting (Samsung Page 21), but does not explicitly reference a live streaming scenario. Referring to claim 3, Brazell does not disclose a method wherein the scenario information includes one or more of a theme of the live streaming, category information of a store to which the live streaming belongs, or an element in the live streaming with which the target user has interacted. Brannon discloses this (Brannon [0041] “…Thus, in the illustrated example, the insurance server 102 may determine that the virtual character 210 has arrived at the virtual kiosk 220, and thus the user 170 is attempting to interact with the virtual insurance kiosk. As another example, the insurance server 102 may detect that the user 170 is attempting to interact with the virtual insurance kiosk by detecting a virtual interaction with the virtual insurance kiosk.”). This noted feature in Brannon is applicable to the method of Brazell in view of Samsung as the prior art references share characteristics and capabilities, namely, they are generally related to virtual environments. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Brazell in view of Samsung as described above because many virtual environments do not provide adequate security for particular types of transactions, and/or do not adequately determine which types of transactions should receive additional security (Brannon [0003]). Referring to claim 4, Brazell does not disclose a method wherein the current scenario is a metaverse, and the digital avatar is a system role in the metaverse. Brannon discloses this (Brannon [0003]). This noted feature in Brannon is applicable to the method of Brazell in view of Samsung as the prior art references share characteristics and capabilities, namely, they are generally related to virtual environments. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Brazell in view of Samsung as described above because many virtual environments do not provide adequate security for particular types of transactions, and/or do not adequately determine which types of transactions should receive additional security (Brannon [0003]). Referring to claim 8, Brazell does not disclose a method according to claim 1, wherein the obtaining the current state data includes fusing source data of a plurality of modes, and the source data of the plurality of modes includes at least two of: text source data, image source data, audio source data, or video source data. Brannon discloses this (Brannon [0076] Additionally, the insurance server 102 may also receive information from other sources. For example, the insurance server 102 may optionally receive house information (350) from house 180. Examples of information received from the house 180 include: images of the inside and/or outside of the house 180, video of the inside and/or outside of the house 180, temperature data of the house, electrical usage of the house, water usage of the house, humidity data of the house, lists of items in the house 180, etc.”). This noted feature in Brannon is applicable to the method of Brazell in view of Samsung as the prior art references share characteristics and capabilities, namely, they are generally related to virtual environments. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Brazell in view of Samsung as described above because many virtual environments do not provide adequate security for particular types of transactions, and/or do not adequately determine which types of transactions should receive additional security (Brannon [0003]). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW S GART whose telephone number is (571)272-3955. The examiner can normally be reached M-F 8:30AM-5:00PM. 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, Tariq Hafiz can be reached at 571-272-5350 . 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. /MATTHEW S GART/Supervisory Patent Examiner, Art Unit 3696
Read full office action

Prosecution Timeline

Nov 21, 2023
Application Filed
Jun 11, 2025
Non-Final Rejection — §102, §103
Sep 10, 2025
Response Filed
Oct 08, 2025
Final Rejection — §102, §103
Jan 14, 2026
Request for Continued Examination
Feb 17, 2026
Response after Non-Final Action
Feb 18, 2026
Non-Final Rejection — §102, §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
9%
Grant Probability
26%
With Interview (+17.2%)
2y 5m
Median Time to Grant
High
PTA Risk
Based on 65 resolved cases by this examiner. Grant probability derived from career allow rate.

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