Prosecution Insights
Last updated: October 02, 2026
Application No. 19/100,660

IMPROVED ACCURACY OF ANALYTICS IN A WIRELESS COMMUNICATIONS NETWORK

Final Rejection §101§102§112
Filed
Feb 03, 2025
Priority
Aug 03, 2022 — GR 20220100633 +1 more
Examiner
LEE, BRYAN Y
Art Unit
Tech Center
Assignee
Lenovo (United States) Inc.
OA Round
2 (Final)
67%
Grant Probability
Favorable
3-4
OA Rounds
2y 3m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 67% — above average
67%
Career Allowance Rate
228 granted / 339 resolved
+7.3% vs TC avg
Strong +41% interview lift
Without
With
+40.6%
Interview Lift
resolved cases with interview
Typical timeline
3y 11m
Avg Prosecution
8 currently pending
Career history
346
Total Applications
across all art units

Statute-Specific Performance

§101
7.2%
-32.8% vs TC avg
§103
56.4%
+16.4% vs TC avg
§102
23.2%
-16.8% vs TC avg
§112
11.2%
-28.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 339 resolved cases

Office Action

§101 §102 §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 . The present application is being examined under the pre-AIA first to invent provisions. 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. Response to Remarks/Arguments This communication is considered fully responsive to the Amendment filed on 07 August 2026. The 35 USC § 102 and 103 rejection(s) of claim(s) 1-9, 12-22 is/are maintained. The 35 USC § 101 rejection(s) to claim(s) 1-9, 12-22 is/are withdrawn since the claim(s) has/have been amended accordingly. Additionally, the amendments has introduced 112(b) indefiniteness issues. See before to detailed rejection. Applicant’s arguments, see Remarks, filed on 07 August 2026, with respect to the rejection(s) of claim(s) ) 1-9, 12-22 under 35 USC § 102 and 103 have been fully considered but they are not persuasive. Upon reconsideration of the current prior art, Khare teaches the amended subject matter. Khare teaches both supplementary data sources and comparing data between data sources. Therefore the rejection is maintained. See below for more detailed rejection. Claim Rejections - 35 USC § 112 The following is a quotation of the first paragraph of 35 U.S.C. 112(a): The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claim(s) 1-9, 12-24 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention. Independent claims 1, 13 and 14 include the language “comparing data from the at least one data source with the supplementary data”. It is unclear which data and which data source this is referring to. “Analytics data” is generated from a data source. However, “data” could be other data from the at least one data source. Also “one data source” could be referring to the first “at least one data source” or the second “one or more data sources”. 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. The claimed invention is directed to non-statutory subject matter. The claim(s) 1-9, 12-22 does/do not fall within at least one of the four categories of patent eligible subject matter because a function and an entity, or methods performed by “function” or “entity” are not processes, machines, manufactures, or compositions of matter. 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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention. (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. Claim(s) 1-9 and 12-22 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by U.S. Pre-Grant Publication US-20230262498-A1 to KHARE et al. (“KHARE”). As to claim 1, KHARE disclose(s) a network equipment (NE) that includes a data analytics function for wireless communication, the NE comprising: at least one memory; and at least one processor coupled with the at least one memory and configured to cause the data analytics function to: generate analytics data for an analytics service using at least one data source; (KHARE; generate analytics from collected data; [0030]) receive an event related to the analytics service; (KHARE; trigger; [0031];) receive supplementary data from one or more other data sources; (KHARE; accuracy report is based on data source and accuracy data collected different sources; [0038]) and determine a rating of the at least one data source, the rating based on comparing data from the at least one data source with the supplementary data. (KHARE; accuracy report based on data source and different source; [0038]; the reports is made by comparing inputs and weighting them based on accuracy; [0032]) As to claim 2, KHARE disclose(s) the data analytics function of claim 1 wherein the at least one processor is further arranged to cause the data analytics function to: identify a rating of the at least one data source as below a predetermined threshold; (KHARE; accuracy below a threshold; [0040]) and trigger a corrective action based at least in part on the at least one data source having the rating below the predetermined threshold. (KHARE; terminate subscription; [0040]) As to claim 3, KHARE disclose(s) the data analytics function of The data analytics function of wherein the corrective action comprises the at least one processor arranged to cause the data analytics function to one or more of: request the supplementary data from one or more other data sources; update a stated accuracy of an analytics report; update a mapping of the one or more other data sources source to the analytics service. (KHARE; terminate or modify the subscription; [0040]) As to claim 4, KHARE disclose(s) the data analytics function of claim 1,wherein the event is received by at least a network data analytics function model training logical function. (KHARE; training; [0031]) As to claim 5, KHARE disclose(s) the data analytics function of claim 1,wherein the at least one data source comprises an application function. (KHARE; NWDAF data analytics function; [0040]) As to claim 6, KHARE disclose(s) the data analytics function of claim 1,wherein, to determine the rating of the at least one data source, the at least one processor is further arranged to cause the data analytics function to verify data from the at least one data source by comparing the data from the at least one data source with the supplementary data. (KHARE; verification of predictions; [0041]) As to claim 7, KHARE disclose(s) the data analytics function of claim 1, wherein, to determine the rating of the at least one data source, the at least one processor is arranged to cause the data analytics function to obtain a data source contribution weight. (KHARE; adjust the weight; [0032]) As to claim 8, KHARE disclose(s) the data analytics function of claim 1, further comprising storing wherein the at least one processor is arranged to cause the data analytics function to store the rating in a data storage entity. KHARE; storing accuracy information; [0051]) As to claim 9, KHARE disclose(s) the data analytics function of claim 1,wherein the at least one processor is arranged to cause the data analytics function to send the rating of the at least one data source to at least one network node. (KHARE; sending accuracy report to consumer; [0011]) As to claim 12, KHARE disclose(s) the data analytics function of claim 1, wherein the rating is further based on previous data source ratings. (KHARE; prior predictions; [0029];[0047]) As to claim 13, KHARE disclose(s) a method performed by a data analytics function, the method comprising: generating analytics data for an analytics service using at least one data source; receiving an event related to the analytics service; and in response to receiving the event, determining a rating of the at least one data source, the rating based on supplementary data. See similar rejection to claim 1. As to claim 14, KHARE disclose(s) a data storage entity comprising: at least one memory; and at least one processor coupled with the at least one memory and arranged to cause the data storage entity to: receive a rating of at least one data source; (KHARE; sending accuracy report to consumer; [0011]) and to store the rating of the at least one data source. (KHARE; storing accuracy information; [0051]) As to claim 15, KHARE disclose(s) the data storage entity of claim 14, wherein the at least one processor is arranged to cause the data storage entity to send the rating of the at least one data source to a data analytics function. (KHARE; NWDAF provide accuracy information ; [0029]) As to claim 16, KHARE disclose(s) a method performed by a data storage entity, the method comprising: receiving a rating of at least one data source; and (KHARE; sending accuracy report to consumer; [0011]) storing the rating of the at least one data source. (KHARE; storing accuracy information; [0051]) See similar rejection to claim 14. As to claim 17, KHARE disclose(s) the method of claim 16, further comprising sending the rating of the at least one data source to a data analytics function. (KHARE; NWDAF provide accuracy information ; [0029]) See similar rejection to claim 15. As to claim 18, KHARE disclose(s) the method of claim 13, further comprising: identifying a rating of the at least one data source as below a predetermined threshold; (KHARE; accuracy below a threshold; [0040]) and triggering a corrective action based at least in part on the at least one data source having the rating below the predetermined threshold. (KHARE; terminate subscription; [0040]) See similar rejection to claim 2. As to claim 19, KHARE disclose(s) the method of claim 18, wherein the corrective action further comprises at least one of: requesting the supplementary data from one or more other data sources; updating a stated accuracy of an analytics report; or updating a mapping of the one or more other data sources to the analytics service. See similar rejection to claim 3. As to claim 20, KHARE disclose(s) the method of claim 13, wherein the determining the rating of the at least one data source further comprises verifying data from the at least one data source by comparing the data from the at least one data source with the supplementary data. See similar rejection to claim 6. As to claim 21, KHARE disclose(s) the method of claim 13, further comprising storing the rating in a data storage entity. See similar rejection to claim 8. As to claim 22, KHARE disclose(s) the method of claim 13, further comprising sending the rating of the at least one data source to at least one network node. See similar rejection to claim 9. As to claim 23, KHARE disclose(s) the method of claim 13, wherein the event is received by at least a network data analytics function model training logical function. (KHARE; ML model training function; [0040];) As to claim 24, KHARE disclose(s) the method of claim 13, wherein the at least one data source comprises an application function. (KHARE; network function; fig. 2; [0039]) Conclusion 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 extension fee 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 BRYAN LEE whose telephone number is (571)270-5606. The examiner can normally be reached on Mon-Fri 9am-5pm. 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, Oscar Louie can be reached on (571) 270-1684. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /BRYAN Y LEE/Primary Examiner, Art Unit 2445
Read full office action

Prosecution Timeline

Feb 03, 2025
Application Filed
May 19, 2026
Non-Final Rejection mailed — §101, §102, §112
Jun 05, 2026
Interview Requested
Jun 12, 2026
Applicant Interview (Telephonic)
Jun 18, 2026
Examiner Interview Summary
Aug 07, 2026
Response Filed
Sep 24, 2026
Final Rejection mailed — §101, §102, §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

3-4
Expected OA Rounds
67%
Grant Probability
99%
With Interview (+40.6%)
3y 11m (~2y 3m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 339 resolved cases by this examiner. Grant probability derived from career allowance rate.

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