Response to Amendment
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 .
This action is responsive to amendment filed on 5/10/24. Claims 1-20 are presented for examination.
Claim Rejections - 35 USC § 102
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 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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Rice et al (USPN. 2019/0363959).
Regarding claims 1, 19 and 20, Rice discloses computing medium, method and system comprising (fig. 1 and 3, par. 64, ingestion and synchronization system):
at least one hardware processor (fig. 2 and 32, data processing system);
at least one memory coupled to the at least one hardware processor (fig. 2 and 32); and
one or more computer readable storage media storing computer-executable instructions that, when executed, cause the computing system to perform operations comprising (figs. 1 and 32):
receiving a request to identify data objects in a cluster (fig. 4 and 11, par. 242, request object), the cluster being associated with an anchor data object and the data objects being members of a first plurality of data objects (figs. 9-11, pars. 243-244, grouping of objects, Account record object);
determining a first data object to serve as the anchor data object, the anchor data object being associated with a semantic context and where other members of the cluster are also associated with the semantic context (figs. 9-12, pars. 234-235, using feature vector, metrics and other matching models to semantically match objects into groups, see par. 243);
determining a second data object, different than the first data object, having a first relationship to the anchor data object (par. 247-249 and 257, two groups of users, account teams and opportunity teams based on related activity), the first relationship being specified in a definition of the second data object (pars. 235-237, matching strategies/rules for record objects);
adding the second data object to the cluster (par. 64, add objects/sync, and pars. 261-262, update matching decisions of groups, companies);
determining a third data object having a second relationship to the anchor data object or a third relationship to the second data object (par. 247-249 and 257, other groups of users across different companies) the second or third relationship being specific in a definition of the third data object (fig. 11 and pars. 148 and 235, rules used for matching specifically business emails, note that plurality of activities and plurality of objects use plurality of rules for tagging/matching different plurality of sets of data);
adding the third data object to the cluster (par. 64, add objects/sync, and pars. 261-262, update matching decisions of groups, companies); and
assigning a name to the cluster (fig. 9, par. 73, assign a name).
2. The computing system of claim 1, wherein the first plurality of data objects are defined in a plurality of software layers and the anchor data object is located at a highest layer of the plurality of software layers (fig. 10, item 1002, Object).
3. The computing system of claim 2, wherein the anchor data object is an only data object in the cluster from the highest layer of the plurality of software layers (fig. 10, item 1002, Object).
4. The computing system of claim 2, wherein the cluster is a first cluster, and a second cluster comprises a fourth data object that is also a member of the first cluster, where the fourth data object is the second data object, the third data object, or is a data object other than the first data object, the second data object, and the third data object (par. 247-249 and 257, other groups of users across different companies comprises a plurality of objects).
5. The computing system of claim 1, wherein the second data object is not directly related to the third data object (fig. 10, items 1004 and 1006, Objects are not directly related as they comprise different field values).
6. The computing system of claim 1, wherein the second data object has the relationship with the third data object and the third data object is analyzed for inclusion in the cluster based at least in part on the relationship (fig. 9 and 11, pars. 261 and 270, policies with different features and models are used to group objects).
7. The computing system of claim 1, wherein the cluster is associated with a cluster identifier, the cluster identifier comprising the name and a use case, the operations further comprising: adding the identifier to the anchor data object, adding the identifier to the second data object, and adding the identifier to the third data object (par. 100, each data point can be associated with a source of the data point identifying an origin of the data point when they are from the same source, i.e., calendar).
8. The computing system of claim 1, wherein the cluster is associated with a cluster identifier and a cluster definition is stored outside of any data object in the cluster, the cluster definition comprising an identifier of the cluster and identifiers of data objects in the cluster (fig. 9, Policy Engine 320, see pars. 110 and 121, policy definitions used to identify activities and the like).
9. The computing system of claim 1, wherein the anchor data object, the second data object, and the third data object are associated with respective timestamps, the operations further comprising: identifying a most recent timestamp associated with data objects in the cluster and assigning the most recent timestamp to the cluster (par. 100, timestamp when the data point was generated or last updated, note that the data item points to the data source).
10. The computing system of claim 1, the operations further comprising: analyzing a second plurality of data objects of the first plurality of data objects for membership in the cluster, wherein the second plurality of data objects comprises all or a portion of the first plurality of data objects, the analyzing comprising determining whether a given data object of the second plurality of data objects is associated with a specified use case, and not adding the given data object to the cluster if the given data object is not associated with the specified use case (fig. 9, item 330, par. 235, restricting rules to refine, discard from candidate objects).
11. The computing system of claim 1, wherein the second relationship comprises an association between the second data object and the third data object or a selection of data from a third data artifact to be included in the second data object (par. 95, common fields and values).
12. The computing system of claim 1, wherein data objects of the first plurality of data objects comprises one or more of logical data objects, views or other data objects in a virtual data model, or database tables or database views (figs. 6A and B).
13. The computing system of claim 1, the operations further comprising: receiving user input defining the anchor data object or receiving user input specifying a data object of the first plurality of data objects to be added to the cluster (figs. 14 and 15, user inputs data).
14. The computing system of claim 1, the operations further comprising: defining a deployment operation based at least in part on the cluster (par. 100, timestamp when the data point was generated or last updated, note that the data item points to the data source).
15. The computing system of claim 11, the operations further comprising: defining a replication operation based at least in part on the cluster (figs. 3 and 9, par. 64, synchronization policy).
16. The computing system of claim 1, the operations further comprising: defining an API to provide access to a plurality of data objects of the first plurality of data objects based at least in part on the cluster (par. 510 API for accessing objects).
17. The computing system of claim 1, wherein the anchor data object comprises an identifier identifying the anchor data object as the anchor data object for the cluster (fig. 9, Policy Engine 320, see pars. 110 and 121, policy definitions used to identify activities and Objects).
18. The computing system of claim 1, wherein a definition of the cluster comprises an identifier identifying the anchor data object for the cluster (figs. 9 and 11, par. 76, managing activities and objects, see also Policy Engine 320, see pars. 110 and 121, policy definitions).
Response to Arguments
Applicant's arguments filed 5/10/24 have been fully considered but they are not persuasive. See remarks below.
Applicant alleges the two amended features in view of the claimed limitations are not taught by the prior art, specifically the object associations.
Examiner disagrees. The relevant portion of the updated OA reads,
“determining a second data object, different than the first data object, having a first relationship to the anchor data object (par. 247-249 and 257, two groups of users, account teams and opportunity teams based on related activity), the first relationship being specified in a definition of the second data object (pars. 235-237, matching strategies/rules for record objects);
adding the second data object to the cluster (par. 64, add objects/sync, and pars. 261-262, update matching decisions of groups, companies);
determining a third data object having a second relationship to the anchor data object or a third relationship to the second data object (par. 247-249 and 257, other groups of users across different companies) the second or third relationship being specific in a definition of the third data object (fig. 11 and pars. 148 and 235, rules used for matching specifically business emails, note that plurality of activities and plurality of objects use plurality of rules for tagging/matching different plurality of sets of data);
Rice clearly is focused on matching/aligning different objects from a plurality of different sources based on specific rules/definitions such as grouping business emails together based on a common activity or a plurality of activities (see pars. 56-57). There can be overlap of rules/definitions and filters may be applied to the activities and objects for different functions (par. 89). This type of use of different rules is used to record objects of systems (par. 148). If applicant believes his objects or rules differ from Rice he is welcome to claim more details.
As such, all allegations are believed moot.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure in the field of organizing/clustering data:
USPN. 2023/0054316: associate objects with cluster: par. 46, figs. 2 and 4
USPN. 2021/0034858: field descriptions and clusters, social network: fig. 4, pars. 29 and 64
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 MARCIN R FILIPCZYK whose telephone number is (571)272-4019. The examiner can normally be reached M-F 7-4 EST.
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, Hosain Alam can be reached on 571-272-3978. 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.
June 6, 2024
/MARCIN R FILIPCZYK/Primary Examiner, Art Unit 2153
Prosecution Insights