Prosecution Insights
Last updated: April 19, 2026
Application No. 18/927,036

METHOD, APPARATUS AND DEVICE FOR GENERATING A CONVERSATION SCENARIO MODEL

Final Rejection §103§112
Filed
Oct 25, 2024
Examiner
SONIFRANK, RICHA MISHRA
Art Unit
2654
Tech Center
2600 — Communications
Assignee
Beijing Waterdrop Technology Group Co. Ltd.
OA Round
4 (Final)
66%
Grant Probability
Favorable
5-6
OA Rounds
3y 3m
To Grant
91%
With Interview

Examiner Intelligence

Grants 66% — above average
66%
Career Allow Rate
250 granted / 379 resolved
+4.0% vs TC avg
Strong +25% interview lift
Without
With
+24.9%
Interview Lift
resolved cases with interview
Typical timeline
3y 3m
Avg Prosecution
29 currently pending
Career history
408
Total Applications
across all art units

Statute-Specific Performance

§101
16.6%
-23.4% vs TC avg
§103
56.1%
+16.1% vs TC avg
§102
11.2%
-28.8% vs TC avg
§112
8.2%
-31.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 379 resolved cases

Office Action

§103 §112
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 . Priority Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55. Response to Amendment Claims 1 and 8 are amended. Claims 2-4 and 9 are cancelled. Claims 1 and 5-8 are presented for examination. Response to Arguments Applicant’s arguments filed on 10/10/2025 have been reviewed. Following are the response: Claim Rejections-35 USC § 112 In light of amendments rejection 35 USC § 112 is withdrawn. Claim Rejections - 35 USC § 103 Applicant argues “Orkin's system is already functionally complete for its purpose of training models based on predefined dialog acts. There is no identified problem or deficiency in Orkin that would motivate a person of ordinary skill to seek a solution from Yu's unrelated field of webpage click analysis. Yu's spatially-defined, static webpage range is fundamentally incompatible with the temporal, dynamic, and semantic nature of a conversation flow in Orkin. Embedding a static, location-based range from a webpage into a conversational AI system to manage event tracking is not a technically sensible or foreseeable combination. The person of ordinary skill would lack any motivation to Page 7 of 9 force Yu's webpage-centric solution into Orkin's conversation-centric problem domain, as they address fundamentally different technological environments” However as stated in the previous motivation, one can be modify the event in the conversation of Orkin to be range based as shown the Yu’s idea of web page interacting with the user and the tracking is range based to identify user behavior more efficiently. Applicant further contends “Even if one were to combine the references, the result would not be the claimed invention. Combining Orkin with Yu might, at best, lead to a system that tracks clicks within a fixed spatial range on a conversation UI element. It would not yield a method where the event-tracking range is determined "based on actual requirements and targets of the conversation scenario", as now claimed. The claimed invention encompasses strategic choices like global tracking, partial-page tracking, or event-triggered tracking, which are strategic decisions based on business or conversational goals, not the static page-location logic of Yu” However In response to applicant's argument it would not yield a method where event tracking range is determined but the fact that the inventor has recognized another advantage which would flow naturally from following the suggestion of the prior art cannot be the basis for patentability when the differences would otherwise be obvious. See Ex parte Obiaya, 227 USPQ 58, 60 (Bd. Pat. App. & Inter. 1985). Further the motivation to use a range based tracking is coming from the secondary reference which is in line with Graham v deere. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, 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. Claims 1, 7 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Orkin ( US 20220122595) and further in view of Yu ( CN 105550184 ) Regarding claim 1, Orkin teaches a method for generating a conversation scenario model, comprising: acquiring a question-answer conversation text formed in a historical information interaction process of a conversation scenario ( Fig 2A, sequence of conversation, Para 0039), wherein the question-answer conversation text comprises multiple rounds of text interaction information ( conversation with turns, Para 0032); defining an event-tracking according the conversation scenario, wherein the event-tracking is determined based on actual requirements and targets of the conversation scenario ( In particular, and at any point in the multi-turn conversation, the data model comprises the observation history, namely, a hierarchical set of events that have been determined to represent the conversation up to at least one conversation turn (and typically many turns)., Para 0051….Para 0063-0066; here the event tracking ( event) based on actual conversation (multi-turn conversation)) , in which event- tracking is added on operation events in an information interaction page, ( event for e.g. acts , Para 0020-0025) , capturing user's behavior data reported by the information interaction page according to the operation events of the event-tracking ( acts by the user, Para 0020-0025) , determining flow attribute information of user's triggering operation behaviors during the information interaction according to the event-tracking records of the process operations in the information interaction page ( fig 2A-2B) , wherein the flow attribute information comprises user's current operation behavior information( fig 2) ; processing the flow attribute information into flagged guide information which is represented by field information according to a preset format ( moment of interest, Para 0034) ; adding the flagged guide information ( metadata including - offer meeting or accepted meeting etc. , Fig 1)into the question-answer conversation text (flag guide metadata which includes a tag associated with observation, key moment step id and instance, Para 0029, 0034, 039), wherein the flagged guide information is the field information obtained by processing the event-tracking records in the information interaction page( for e.g. tag associated with the physical act, physical act can be clicking event, Para 0024, 0051, Fig 1, Fig 2), wherein the adding flagged guide information into the question-answer conversation text comprises: adding the event-tracking in the information interaction page to capture each behavior operation triggered by a user ( for e.g. user accepting a meeting Para 0011, 0039), generating the flagged guide information in the way of the event-tracking records ( tagging/flagging, Para 0011, 0039), and adding the flagged guide information to the question-answer conversation text as a guideline label of process operations( fig 2A, 2B, Fig 4, Fig 7); and performing model training by using the question-answer conversation text with the flagged guide information to generate an information interaction model of the conversation scenario( training a model, Fig 1, Para 0029), wherein the question-answer conversation text with the flagged guide information has a guiding effect on the process operations in the information interaction page ( output metadata where metadata is a tag wherein tag includes observation and based on the observation conversation proceeds as in fig 6, Para 0029), and wherein on the basis of model training with the question-answer conversation text, the flagged guide information with control capability in multi-round interaction sis added to activate process control capability of the information interaction model(based on the observation conversation proceeds, Para 0029, Fig 1, Fig 6), so that the generated information interaction model guides the process operations in the conversation scenario( fig 2A, 2B, Fig 5-6) Orkin does not explicitly teaches defining an event-tracking range according to the conversation scenario, in which event- tracking is added on operation events in an information interaction page, wherein the operation events at least comprise page events and click events; capturing user's behavior data reported by the information interaction page according to the operation events of the event-tracking, in response to a triggering instruction of the operation events of the event-tracking in the information interaction page; restoring user's operation behaviors in the information interaction process according to the user's behavior data to obtain event-tracking records of process operations in the information interaction process; determining flow attribute information of user's triggering operation behaviors during the information interaction according to the event-tracking records of the process operations in the information interaction page, wherein the flow attribute information comprises user's current operation behavior information and next round of interaction behavior information triggered by the current operation behavior; processing the flow attribute information into flagged guide information which is represented by field information according to a preset format; However in the same field of endeavor Yu teaches defining an event-tracking range according to the conversation scenario( clickable point can be buried ( range), first and last buried points ( clickable), Para 0072), Yu) , capturing user's behavior data reported by the information interaction page according to the operation events of the event-tracking ( user behavior for e.g. what user clicked conversion rate based on adjacent buried points etc., Para 0072) , in response to a triggering instruction of the operation events of the event-tracking in the information interaction page ( clicks, Para 0072) ; restoring user's operation behaviors in the information interaction process according to the user's behavior data to obtain event-tracking records of process operations in the information interaction process (capturing user behavior and embed is created based on user behavior, Para 0037-0042, 0072, Yu); determining flow attribute information of user's triggering operation behaviors during the information interaction according to the event-tracking records of the process operations in the information interaction page ( for e.g. order in which user will complete the task, Para0042-0045) , wherein the flow attribute information comprises user's current operation behavior information and next round of interaction behavior information triggered by the current operation behavior( user clicks and task to complete next round , Para 0042-0045, 0072-0073, Yu); processing the flow attribute information into flagged guide information which is represented by field information according to a preset format ( display the analysis based on date, 0071, 0075, Yu) It would have been obvious having the teachings of Orkin to further include the concept of Yu before effective filing date because by doing so the process would know which kind of events to track to identify user’s behavior to improve efficiency ( Para 0083, Yu) Regarding claim 7, Orkin as above in claim 1, teaches wherein the text interaction information of each round comprises input conversation text and output conversation text, and after the performing model training by using the question-answer conversation text with the flagged guide information to generate an information interaction model of the conversation scenario ( model training with annotation, Fig 1, Para 0006) , the method further comprises: acquiring an input conversation text of current round in response to an information interaction instruction triggered by the conversation scenario ( for e.g. event type, Fig 6) ; inputting the input conversation text of current round into the information interaction model for prediction ( inputting the text, Fig 6) , and obtaining an output conversation text of current round for interaction feedback; and controlling information interaction process of next round according to the output conversation text of current round ( Para 0071-0073, element 612, Fig 6) Regarding claim 8, arguments analogous to claim 1, are applicable. Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Orkin ( US 20220122595) and further in view of Yu ( CN 105550184 ) and further in view of Ji (US Pub: 20210005190 ) Regarding claim 5, Orkin as above in claim 1, teaches wherein the adding flagged guide information into the question-answer conversation text comprises: defining a flag at a corresponding field position in the question-answer conversation text according to an event-tracking position (for e.g. offer meeting) of the conversation scenario in the information interaction page ( adding a special flag for e.g. clicking event or offer meeting etc., Fig 2) ; and adding the flagged guide information into the question-answer conversation text by using the special embedded flag (fig 2-5) Orkin does not explicitly teaches defining a special embedding flag However Ji teaches defining a special embedding flag for specific transcriptions (embed private speech indicator(flag), Para 0051-0052, 0057; wherein the private transcription are conversations according to event tracking position) It would have been obvious having the teachings of Orkin and Yu to have the concept of Ji to provide a secured indicator since its known in the art that embedding increases security Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Orkin ( US 20220122595) and further in view of Yu ( CN 105550184 ) and further in view of Huang ( CN 116909453 ) Regarding claim 6, Orkin as above in claim 1, teaches wherein the performing model training by using the question-answer conversation text with the flagged guide information to generate an information interaction model of the conversation scenario comprises: performing model training by using the question-answer conversation text with the flagged guide information, and strengthening the control capability of the process operations in the conversation scenario according to the flagged guide information in the training process ( model training based on annotation, Para 0029, Fig 1 and Fig 5) ; and wherein the information interaction model is used for generating an output conversation text with process operation guidance according to an input conversation text ( Fig 6) Orkin does not explicitly teach determining the trained neural network model as the information interaction model of the conversation scenario when the iteration of the model training meets a preset condition, However Huang teaches determining the trained neural network model as the information interaction model of the conversation scenario when the iteration of the model training meets a preset condition, wherein the information interaction model is used for generating an output conversation text with process operation guidance according to an input conversation text ( based on the difference between the output result and the marked text label, performing iterative adjustment on the initial text interaction model, until the difference satisfies the preset requirement, obtaining a text identification model, wherein the proportion of the text data of the pre-set account in the text data sample corresponding to each iteration of the model is greater than or equal to the pre-set threshold; wherein the model is a neural network model, Page 2, last Para; Page 3 Para 1-7) It would have been obvious having the teachings of Orkin and Yu to further include the concept of Huang before effective filing date so that the intelligent customer service can perform accurate feedback based on the interactive text, therefore, and questions can be answered more accurately ( Page 2, Para 2) Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Visual Analytics of Anomalous User Behaviors: A Survey discloses --By analyzing patterns in user-specified spatial and temporal ranges, analysts study user behaviors in multiple levels of granularity, and gradually develop their understanding during interactive exploration THIS ACTION IS MADE FINAL. 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 Richa Sonifrank whose telephone number is (571)272-5357. The examiner can normally be reached M-T 7AM - 5:30PM. 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, Phan Hai can be reached at (571)272-6338. 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. /Richa Sonifrank/Primary Examiner, Art Unit 2654
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Prosecution Timeline

Oct 25, 2024
Application Filed
Jan 03, 2025
Non-Final Rejection — §103, §112
Mar 04, 2025
Response Filed
Mar 12, 2025
Final Rejection — §103, §112
Jun 02, 2025
Response after Non-Final Action
Jul 15, 2025
Request for Continued Examination
Jul 17, 2025
Response after Non-Final Action
Aug 14, 2025
Non-Final Rejection — §103, §112
Oct 10, 2025
Response Filed
Oct 26, 2025
Final Rejection — §103, §112 (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

5-6
Expected OA Rounds
66%
Grant Probability
91%
With Interview (+24.9%)
3y 3m
Median Time to Grant
High
PTA Risk
Based on 379 resolved cases by this examiner. Grant probability derived from career allow rate.

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