Office Action Predictor
Last updated: April 15, 2026
Application No. 18/521,035

INFORMATION PROCESSING APPARATUS, CONTROL METHOD OF INFORMATION PROCESSING APPARATUS, AND STORAGE MEDIUM

Final Rejection §102§103
Filed
Nov 28, 2023
Examiner
SAINT CYR, LEONARD
Art Unit
2658
Tech Center
2600 — Communications
Assignee
Canon Kabushiki Kaisha
OA Round
2 (Final)
77%
Grant Probability
Favorable
3-4
OA Rounds
3y 1m
To Grant
98%
With Interview

Examiner Intelligence

Grants 77% — above average
77%
Career Allow Rate
882 granted / 1144 resolved
+15.1% vs TC avg
Strong +21% interview lift
Without
With
+21.2%
Interview Lift
resolved cases with interview
Typical timeline
3y 1m
Avg Prosecution
32 currently pending
Career history
1176
Total Applications
across all art units

Statute-Specific Performance

§101
17.8%
-22.2% vs TC avg
§103
39.1%
-0.9% vs TC avg
§102
28.0%
-12.0% vs TC avg
§112
2.2%
-37.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1144 resolved cases

Office Action

§102 §103
DETAILED ACTION 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 . Response to Arguments Applicant’s arguments, see pages 6, 7, filed 11/17/25, with respect to claims 1 – 4, 6 - 11 have been fully considered and are persuasive. The rejection of claims 1 – 4, 6 – 11 under 35 U.S.C 101 has been withdrawn. Applicant argues that the Amended Claims improve upon conventional display systems by automatically extracting entities using AI/ML technology, determining conceptual relationships between generic and specific concepts, and conditionally controlling display based on similarity matching with stored preferences. This is not a generic "apply it on a computer" addition but a specific technical solution to the problem of intelligently displaying extracted information based on learned user preferences and conceptual relationships (Amendment, pages 6, 7). Applicant's arguments filed 11/17/2025 have been fully considered but they are not persuasive. Applicant argues that claims 1, 10, 11 distinguish over the applied references and are in condition for allowance by incorporating the subject matter of claim 6 (Amendment, page 8). The examiner disagrees, and points out that most of the limitations of claim 6 are not incorporated into claims 1, 10, and 11. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1 – 4, 6, and 9 – 11 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Shen et al. (US PAP 2011/0022292). As per claims 1, 10, 11, Shen et al. teach an information processing apparatus/method comprising: a storage unit configured to store a plurality of named entities in association with information indicating whether to display the plurality of named entities (“The geographic information provided by the GPS and/or the user may be used to construct a weighting hierarchy for proper names in the database so that prioritized name categories at different levels may be used to assist speech recognition.”; paragraphs 7, 8); one or more processors coupled to a memory that function as (paragraphs 29, 30): an extraction unit configured to extract a plurality of entities by inputting document data to a named entity recognition model (“The geographic information provided by the GPS and/or the user may be used to construct a weighting hierarchy for proper names in the database so that prioritized name categories at different levels may be used to assist speech recognition…A plurality of candidate words are extracted from the geographical information. First ones of the candidate words are extracted from the first category of geographical information. Second ones of the candidate words are extracted from the second category of geographical information.”; paragraphs 7 – 13); a determination unit configured to determine whether each of the extracted plurality of named entities represents a generic concept or a specific concept (paragraphs 33 – 39); and a display control unit configured to display the extracted plurality of named extracted unit entities in a relationship between the generic concept and the specific concept on a UI screen of a display device (“The geographic information, the static database, and the dynamic active list may be used to establish a set of hierarchical name categories with different priorities in order to facilitate speech recognition. A search index may be used to speed up the generation of prioritized name categories…a set of hierarchical name categories with different weight values for use in speech recognition; geographic information derived from a visible display map and from user gestures; and a search index to speed up the generation of prioritized name categories.”; paragraphs 33 – 36, 42 – 45); wherein the display control unit: displays one of the extracted plurality of named entities representing the generic concept based on information on one of the stored plurality of named entities representing the generic concept, in a case where the one of the extracted plurality of named entities is similar to the one of the stored plurality of named entities; and displays one of the extracted plurality of named entities representing the specific concept based on information on one of the stored plurality of named entities representing the specific concept, in a case where the one of the stored plurality of named entities is a named entity which is most similar to the one of the extracted plurality of named entities (“system with multimodal interfaces including natural language and touch screen, four levels of categories may be identified with priorities in increasing order. That is, the fourth category may be highest priority; the third category may be second highest priority; the second category may be third highest priority; and the first category may be lowest priority. The first category may include a static background database that contains all possible proper names such as street names and POI names… The fourth and last category may include proper names in an active list which could be a list of POIs which have been recently retrieved from the database and are being displayed, have been recently displayed”; paragraphs 33 – 39). As per claim 2, Shen et al. further disclose the display control unit displays the plurality of the named entities by dividing into the determined generic concept or the determined specific concept (“including natural language and touch screen, four levels of categories may be identified with priorities in increasing order. That is, the fourth category may be highest priority; the third category may be second highest priority; the second category may be third highest priority; and the first category may be lowest priority. The first category may include a static background database that contains all possible proper names such as street names and POI names…a set of hierarchical name categories with different weight values for use in speech recognition; geographic information derived from a visible display map and from user gestures; and a search index to speed up the generation of prioritized name categories.”; paragraphs 33 – 36, 42 – 45). As per claim 3, Shen et al. further disclose in a case where there are a generic concept level and a specific concept level in the plurality of the named entities determined to be the specific concept, the display control unit displays the named entity at the generic concept level at a position closer to the named entity determined to be the generic concept (“The second category may include proper names related to geographic entities (e.g., street, POI) contained in the map area that is displayed. For example, if the current map displayed on the screen is of a certain part of a city, then street names and POI names in this area of the city which is visible to the user are put in the second category. These street names and POI names which are in the displayed area of the city may be provided with a higher weighting than are the street names and POI names that are not in this displayed area…a set of hierarchical name categories with different weight values for use in speech recognition; geographic information derived from a visible display map and from user gestures; and a search index to speed up the generation of prioritized name categories.”; paragraphs 33 – 36, 42 – 45). As per claim 4, Shen et al. further disclose the extracted plurality of the named entities is stored in association with the information based on user instructions (“The number of final candidate names presented to the user may depend on a degree of confidence that processor 18 has in the top-ranked final candidate names. For example, processor 18 may display to the user only the top-ranked final candidate name(s) whose sum total probability of matching the user's intended interpretation exceeds some threshold probability, such as 95 percent”; paragraphs 55, 56). As per claim 6, Shen et al. further disclose calculates a similarity between each of the stored plurality of named entities representing the specific concept and each of the extracted plurality of named entities representing the specific concept (“The preliminary candidate interpretations on list 20 may match, or be similar to, POIs, streets, or other proper names provided in geographic information 12. List 20 may be re-ordered by Post-processor 18 to give greater weighting to those preliminary candidate interpretations that match, or are similar to, POIs, streets, or other proper names provided in geographic information”; paragraphs 28, 29). As per claim 9, Shen et al. further disclose the document data is generated by performing character recognition processing for a document (paragraphs 7 -13, 28, 29). 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. Claims 7, 8 are rejected under 35 U.S.C. 103 as being unpatentable over Shen et al. (US PAP 2011/0022292) in view of Bay et al (US 2024/0242032). As per claim 7, Shen et al. do not specifically teach the similarity is calculated by using cosine similarity between a characteristic amount vector of each of the extracted plurality of named entities and a characteristic amount vector of each of the stored plurality of named entities. Bay et al. disclose providing a visual illustration of the unsupervised named entity recognition procedure using representative vectors generated for a reference named entity list. As noted previously, the analysis engine 214 may receive a set of text 702 and may tokenize the set of text to produce a set of input tokens 704. For each input token 704, a corresponding token vector 706 may be generated. Subsequently, the analysis engine 214 may calculate the cosine similarity score between an individual token vector 706 and every representative vector for the reference named entity list. The highest similarity score from all of the cosine similarity calculations is then compared with a predefined decision threshold (paragraph 82). Therefore, it would have been obvious to one of ordinary skill before the effective filing date of the claimed invention to use cosine similarity as taught by Bay et al. in Shen et al., because that would help provide an improved named entity recognition (paragraph 24). As per claim 8, Shen et al. in view of Bay et al. further disclose the characteristic amount vector is an average of characteristic amount vectors of each named entity token (Bay et al., paragraphs 25, 29, 80 – 89). Conclusion 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 LEONARD SAINT-CYR whose telephone number is (571)272-4247. The examiner can normally be reached Monday- Friday. 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, Richemond Dorvil can be reached at (571)272-7602. 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. /LEONARD SAINT-CYR/ Primary Examiner, Art Unit 2658
Read full office action

Prosecution Timeline

Nov 28, 2023
Application Filed
Jul 15, 2025
Non-Final Rejection — §102, §103
Nov 17, 2025
Response Filed
Feb 11, 2026
Final Rejection — §102, §103
Apr 07, 2026
Response after Non-Final Action

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12597415
VOICE RECOGNITION GRAMMAR SELECTION BASED ON CONTEXT
2y 5m to grant Granted Apr 07, 2026
Patent 12592227
DIALOG UNDERSTANDING DEVICE AND DIALOG UNDERSTANDING METHOD
2y 5m to grant Granted Mar 31, 2026
Patent 12591765
SYSTEMS AND METHODS FOR BUILDING A CUSTOMIZED GENERATIVE ARTIFICIAL INTELLIGENT PLATFORM
2y 5m to grant Granted Mar 31, 2026
Patent 12585884
DIALOGUE APPARATUS, DIALOGUE METHOD, AND PROGRAM
2y 5m to grant Granted Mar 24, 2026
Patent 12581180
SPEAKER-DEPENDENT VOICE-ACTIVATED CAMERA SYSTEM
2y 5m to grant Granted Mar 17, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

3-4
Expected OA Rounds
77%
Grant Probability
98%
With Interview (+21.2%)
3y 1m
Median Time to Grant
Moderate
PTA Risk
Based on 1144 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in for Full Analysis

Enter your email to receive a magic link. No password needed.

Free tier: 3 strategy analyses per month