Prosecution Insights
Last updated: April 19, 2026
Application No. 18/790,569

TECHNOLOGIES FOR PERFORMING ATTRIBUTE CONSTRAINED QUERIES FOR REAL-TIME EVENT FLOW VISUALIZATIONS AND ANALYTICS

Non-Final OA §DP
Filed
Jul 31, 2024
Examiner
ARJOMANDI, NOOSHA
Art Unit
2166
Tech Center
2100 — Computer Architecture & Software
Assignee
Genesys Cloud Services Inc.
OA Round
1 (Non-Final)
86%
Grant Probability
Favorable
1-2
OA Rounds
2y 10m
To Grant
96%
With Interview

Examiner Intelligence

Grants 86% — above average
86%
Career Allow Rate
547 granted / 635 resolved
+31.1% vs TC avg
Moderate +10% lift
Without
With
+9.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
15 currently pending
Career history
650
Total Applications
across all art units

Statute-Specific Performance

§101
19.4%
-20.6% vs TC avg
§103
44.1%
+4.1% vs TC avg
§102
20.6%
-19.4% vs TC avg
§112
4.8%
-35.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 635 resolved cases

Office Action

§DP
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 instant office action having application number 18/790569, filed on July 31, 2024, has claims 1-20 pending in this application. Information Disclosure Statement The information disclosure statement (IDS) submitted on 07/31/2024. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Double Patenting The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of U.S. Publication No.2026/0037494. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 1-20 under examination are obvious, respectively, by claims 1-20 of the reference U.S. Publication. Every limitations in the instant application under examination claims are recited in the conflicting reference patent claims, and the differences or additional limitations between the claims are highlighted below by underlining and bolding all limitations. Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the independent claim 1 of the instant application to inserting, by the computing system, a sequence identifier corresponding to each event sequence of the plurality of event sequences into the attribute constraint search structure as a pointer value of the plurality of pointer values, wherein the sequence identifier corresponding to each event sequence is indicative of the fixed positional order maintained by each event pattern set for each event sequence; and inserting, by the computing system, each attribute associated with each singleton event into the attribute constraint search structure as a key value of the plurality of key values. Note, such deviation would not interfere with the functionality of the claims and would achieve the same end result. Please, see the comparison table below: Instant Application 18/790569 Co-pending Application 18790560 1. A method for performing attribute constrained queries for real-time event sequence visualization, the method comprising: retrieving, by a computing system, an event sequence dataset, wherein the event sequence dataset includes data for a plurality of event sequences and a plurality of events, and wherein each event sequence of the plurality of events sequences includes at least one event; determining, by the computing system, a plurality of singleton events from the plurality of events included in the event sequence dataset, wherein each singleton event is associated with an attribute; generating, by the computing system, a plurality of event pattern sets, wherein each event pattern set corresponds to a distinct singleton event and maintains a fixed positional order for each event sequence, and wherein each event pattern set includes pattern occurrence data for each event sequence arranged according to the fixed positional order; generating, by the computing system, a forward search index including each event pattern set corresponding to each distinct singleton event of the plurality of singleton events; identifying, by the computing system, the fixed positional order maintained by each event pattern set for each event sequence; generating, by the computing system, an attribute constraint search structure including a plurality of keys and a plurality of pointer values, wherein each pointer value of the plurality of pointer values is associated with one or more key values of the plurality of key values; inserting, by the computing system, a sequence identifier corresponding to each event sequence of the plurality of event sequences into the attribute constraint search structure as a pointer value of the plurality of pointer values, wherein the sequence identifier corresponding to each event sequence is indicative of the fixed positional order maintained by each event pattern set for each event sequence; and inserting, by the computing system, each attribute associated with each singleton event into the attribute constraint search structure as a key value of the plurality of key values. 9. A system for performing attribute constrained queries for real-time event sequence visualization, the system comprising: at least one processor; and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to: retrieve an event sequence dataset, wherein the event sequence dataset includes data for a plurality of event sequences and a plurality of events, and wherein each event sequence of the plurality of events sequences includes at least one event; determine a plurality of singleton events from the plurality of events included in the event sequence dataset, wherein each singleton event is associated with an attribute; generate a plurality of event pattern sets, wherein each event pattern set corresponds to a distinct singleton event and maintains a fixed positional order for each event sequence, and wherein each event pattern set includes pattern occurrence data for each event sequence arranged according to the fixed positional order; generate a forward search index that includes each event pattern set corresponding to each distinct singleton event of the plurality of singleton events; identify the fixed positional order maintained by each event pattern set for each event sequence; generate an attribute constraint search structure that includes a plurality of keys and a plurality of pointer values, wherein each pointer value of the plurality of pointer values is associated with one or more key values of the plurality of key values; insert a sequence identifier corresponding to each event sequence of the plurality of event sequences into the attribute constraint search structure as a pointer value of the plurality of pointer values, wherein the sequence identifier corresponding to each event sequence is indicative of the fixed positional order maintained by each event pattern set for each event sequence; and insert each attribute associated with each singleton event into the attribute constraint search structure as a key value of the plurality of key values. 9. A system for performing attribute constrained queries for real-time event sequence visualization, the system comprising: at least one processor; and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to: retrieve an event sequence dataset, wherein the event sequence dataset includes data for a plurality of event sequences and a plurality of events, and wherein each event sequence of the plurality of events sequences includes at least one event; determine a plurality of singleton events from the plurality of events included in the event sequence dataset, wherein each singleton event is associated with an attribute; generate a plurality of event pattern sets, wherein each event pattern set corresponds to a distinct singleton event and maintains a fixed positional order for each event sequence, and wherein each event pattern set includes pattern occurrence data for each event sequence arranged according to the fixed positional order; generate a forward search index that includes each event pattern set corresponding to each distinct singleton event of the plurality of singleton events; identify the fixed positional order maintained by each event pattern set for each event sequence; generate an attribute constraint search structure that includes a plurality of keys and a plurality of pointer values, wherein each pointer value of the plurality of pointer values is associated with one or more key values of the plurality of key values; insert a sequence identifier corresponding to each event sequence of the plurality of event sequences into the attribute constraint search structure as a pointer value of the plurality of pointer values, wherein the sequence identifier corresponding to each event sequence is indicative of the fixed positional order maintained by each event pattern set for each event sequence; and insert each attribute associated with each singleton event into the attribute constraint search structure as a key value of the plurality of key values. constraint. 17. One or more non-transitory machine-readable storage media comprising a plurality of instructions stored thereon that, in response to execution by a computing system, causes the computing system to: retrieve an event sequence dataset, wherein the event sequence dataset includes data for a plurality of event sequences and a plurality of events, and wherein each event sequence of the plurality of events sequences includes at least one event; determine a plurality of singleton events from the plurality of events included in the event sequence dataset, wherein each singleton event is associated with an attribute; generate a plurality of event pattern sets, wherein each event pattern set corresponds to a distinct singleton event and maintains a fixed positional order for each event sequence, and wherein each event pattern set includes pattern occurrence data for each event sequence arranged according to the fixed positional order; generate a forward search index that includes each event pattern set corresponding to each distinct singleton event of the plurality of singleton events; identify the fixed positional order maintained by each event pattern set for each event sequence; generate an attribute constraint search structure that includes a plurality of keys and a plurality of pointer values, wherein each pointer value of the plurality of pointer values is associated with one or more key values of the plurality of key values; insert a sequence identifier corresponding to each event sequence of the plurality of event sequences into the attribute constraint search structure as a pointer value of the plurality of pointer values, wherein the sequence identifier corresponding to each event sequence is indicative of the fixed positional order maintained by each event pattern set for each event sequence; insert each attribute associated with each singleton event into the attribute constraint search structure as a key value of the plurality of key values; receive a search request that includes an attribute constraint; search the attribute constraint search structure to identify one or more key values of the plurality of key values that satisfy the attribute constraint; determine, within the attribute constraint search structure, one or more pointer values associated with the one or more key values of the plurality of key values that satisfy the attribute constraint; and output the sequence identifier associated with each of the determined one or more pointer values. 1. (Currently Amended) A method for performing time constrained queries for real- time event sequence visualization, the method comprising: retrieving, by a computing system, an event sequence dataset, wherein the event sequence dataset includes data for a plurality of event sequences and a plurality of events, and wherein each event sequence of the plurality of events event sequences includes at least two sequentially occurring events; generating, by the computing system, a forward search index including a plurality of event pattern sets, wherein each event pattern set corresponds to a respective pattern of events derived from the plurality of event sequences and includes pattern occurrence data for each event sequence of the plurality of event sequences, and wherein the pattern occurrence data for each event sequence is positioned within each event pattern set according to a fixed positional order; identifying, by the computing system, the fixed positional order of each event sequence positioned within each event pattern set of the plurality of event pattern sets of the forward search index; generating, by the computing system, a time constraint search structure including a plurality of keys and a plurality of pointer values, wherein each pointer value of the plurality of pointer values is associated with one or more key values of the plurality of key values; inserting, by the computing system, a sequence identifier corresponding to each event sequence of the plurality of event sequences into the time constraint search structure as a pointer value of the plurality of pointer values, wherein the sequence identifier corresponding to each event sequence is indicative of the fixed positional order of the event sequence within each of the plurality of event patterns sets of the forward search index; and inserting, by the computing system, time interval data for the at least two sequentially occurring events of each event sequence into the time constraint search structure as a key value associated with a respective pointer value for the corresponding event sequence, wherein the time interval data for the at least two sequentially occurring events of each event sequence is indicative of an amount of time elapsed between an occurrence of each of the at least two sequentially occurring events of the event sequence. 9. (Currently Amended) A system for performing time constrained queries for real- time event sequence visualization, the system comprising: at least one processor; and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to: retrieve an event sequence dataset, wherein the event sequence dataset includes data for a plurality of event sequences and a plurality of events, and wherein each event sequence of the plurality of events event sequences includes at least two sequentially occurring events; generate a forward search index that includes a plurality of event pattern sets, wherein each event pattern set corresponds to a respective pattern of events derived from the plurality of event sequences and includes pattern occurrence data for each event sequence of the plurality of event sequences, and wherein the pattern occurrence data for each event sequence is positioned within each event pattern set according to a fixed positional order; identify the fixed positional order of each event sequence positioned within each event pattern set of the plurality of event pattern sets of the forward search index; generate a time constraint search structure that includes a plurality of keys and a plurality of pointer values, wherein each pointer value of the plurality of pointer values is associated with one or more key values of the plurality of key values; insert a sequence identifier that corresponds to each event sequence of the plurality of event sequences into the time constraint search structure as a pointer value of the plurality of pointer values, wherein the sequence identifier that corresponds to each event sequence is indicative of the fixed positional order of the event sequence within each of the plurality of event patterns sets of the forward search index; and insert time interval data for the at least two sequentially occurring events of each event sequence into the time constraint search structure as a key value associated with a respective pointer value for the corresponding event sequence, wherein the time interval data for the at least two sequentially occurring events of each event sequence is indicative of an amount of time elapsed between an occurrence of each of the at least two sequentially occurring events of the event sequence. 17. (Currently Amended) One or more non-transitory machine-readable storage media comprising a plurality of instructions stored thereon that, in response to execution by a computing system, causes the computing system to: retrieve an event sequence dataset, wherein the event sequence dataset includes data for a plurality of event sequences and a plurality of events, and wherein each event sequence of the plurality of events event sequences includes at least two sequentially occurring events; generate a forward search index that includes a plurality of event pattern sets, wherein each event pattern set corresponds to a respective pattern of events derived from the plurality of event sequences and includes pattern occurrence data for each event sequence of the plurality of event sequences, and wherein the pattern occurrence data for each event sequence is positioned within each event pattern set according to a fixed positional order; identify the fixed positional order of each event sequence positioned within each event pattern set of the plurality of event pattern sets of the forward search index; generate a time constraint search structure that includes a plurality of keys and a plurality of pointer values, wherein each pointer value of the plurality of pointer values is associated with one or more key values of the plurality of key values; insert a sequence identifier that corresponds to each event sequence of the plurality of event sequences into the time constraint search structure as a pointer value of the plurality of pointer values, wherein the sequence identifier that corresponds to each event sequence is indicative of the fixed positional order of the event sequence within each of the plurality of event patterns sets of the forward search index; insert time interval data for the at least two sequentially occurring events of each event sequence into the time constraint search structure as a key value associated with a respective pointer value for the corresponding event sequence, wherein the time interval data for the at least two sequentially occurring events of each event sequence is indicative of an amount of time elapsed between an occurrence of each of the at least two sequentially occurring events of the event sequence; receive a search request that includes a time interval constraint; search the time constraint search structure to identify one or more key values of the plurality of key values that satisfy the time interval constraint; determine, within the time constraint search structure, one or more pointer values associated with the one or more key values of the plurality of key values that satisfy the time interval constraint; and output the sequence identifier associated with each of the determined one or more pointer values. "A later patent claim is not patentably distinct from an earlier patent claim if the later claim is obvious over, or anticipated by, the earlier claim. In re Longi, 759 F.2d at 896, 225 USPQ at 651 (affirming a holding of obviousness-type double patenting because the claims at issue were obvious over claims in four prior art patents); In re Berg, 140 F.3d at 1437, 46 USPQ2d at 1233 (Fed. Cir. 1998) (affirming a holding of obviousness-type double patenting where a patent application claim to a genus is anticipated by a patent claim to a species within that genus). " ELI LILLY AND COMPANY v BARR LABORATORIES, INC., United States Court of Appeals for the Federal Circuit, ON PETITION FOR REHEARING EN BANC (DECIDED: May 30, 2001). The application claim 1 does not contain specific limitations as shown in the patent claim 1; however, according to In re Goodman, the application claim 1 is generic to the species of information covered by claim 1 of the co-pending application. Thus, the generic invention is anticipated by the species of the patented invention. The application claim 9 does not contain specific limitations as shown in the patent claim 9; however, according to In re Goodman, the application claim 9 is generic to the species of information covered by claim 9 of the co-pending application. Thus, the generic invention is anticipated by the species of the patented invention. The application claim 17 does not contain specific limitations as shown in the patent claim 17; however, according to In re Goodman, the application claim 17 is generic to the species of information covered by claim 17 of the co-pending application. Thus, the generic invention is anticipated by the species of the patented invention. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to NOOSHA ARJOMANDI whose telephone number is (571)272-9784. The examiner can normally be reached on (571)272-9784. 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, Sanjiv Shah can be reached on (571)272-4098. 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 http://pair-direct.uspto.gov. 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. March 6, 2026 /NOOSHA ARJOMANDI/Primary Examiner, Art Unit 2166
Read full office action

Prosecution Timeline

Jul 31, 2024
Application Filed
Mar 07, 2026
Non-Final Rejection — §DP (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12596732
GENERATIVE ARTIFICIAL INTELLIGENCE (AI) CONSTRUCTION SPECIFICATION INTERFACE
2y 5m to grant Granted Apr 07, 2026
Patent 12591555
SYSTEM AND METHODS FOR LIVE DATA MIGRATION
2y 5m to grant Granted Mar 31, 2026
Patent 12587510
SYSTEMS AND METHODS FOR MANAGED DATA TRANSFER
2y 5m to grant Granted Mar 24, 2026
Patent 12580782
SYSTEMS AND METHODS FOR PROCESSING BLOCKCHAIN TRANSACTIONS
2y 5m to grant Granted Mar 17, 2026
Patent 12572812
GRAPH NEURAL NETWORKS FOR PARTICLE ACCELERATOR FACILITIES
2y 5m to grant Granted Mar 10, 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

1-2
Expected OA Rounds
86%
Grant Probability
96%
With Interview (+9.9%)
2y 10m
Median Time to Grant
Low
PTA Risk
Based on 635 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

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

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month