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 .
Claim Rejections - 35 USC § 112
Claims 20-21, 13-14, and 6-7 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 20, 13, and 6 recites the limitation " for the LLM requesting predictive data sets.” However, claims 2, 9, and 16 recite “large language model (LLM)” in an alternative form (See: “include a cluster based model or large language model (LLM)” in claims 2, 9, and 16). Therefore, there is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 103
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.
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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 – 21 are rejected under 35 U.S.C. 103 as being unpatentable over SAP SE (SAP hereinafter) (EP 4109296; published December 28, 2022) in view of Darrah et al. (US 2022/0414526).
Regarding Claims 15, 8, and 1, SAP discloses a system, comprising:
a processor (Fig. 6, 628, 636, SAP); and
a non-transitory computer readable medium, comprising instructions for (Fig. 6, SAP):
storing raw data received from one or more data sources at a data management system, the raw data stored in the form data is received from each of the one or more data sources ([0018], SAP);
generating a set of predicted data sets based on a predictive model, wherein each of the predictive data sets is associated with a criteria and defines data associated with a criteria that is predicted to be accessed in the future time period ([0019], SAP);
in advance of a request for that data defined by the predictive data sets, obtaining stored raw data associated with selected ones of the set of predicted data sets based on the criteria and time period (Fig. 4, 404, SAP); and
indexing the obtained stored raw data for search at the data management system (Fig. 4, 416, SAP).
However, SAP does not expressly disclose that the predictive data sets associated with a time period and defines data associated with time period that is predicted to be accessed in a future time period. Darrah discloses: that the predictive data sets associated with a time period and defines data associated with time period that is predicted to be accessed in a future time period ([0069], Darrah). It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the system of SAP by incorporating the predictive data sets associated with a time period and defines data associated with time period that is predicted to be accessed in a future time period, as disclosed by Darrah, in order to be able to plan computing resources usage in advance by aligning their capacity with demand. See: KSR International Co. v. Teleflex Inc., 82 USPQ 1385, 1396 (US 2007); MPEP § 2143.
Regarding Claims 16, 9, and 2, SAP/Darrah discloses a system, wherein the predictive model include a cluster based model or a large language model ([0019], SAP; and [0047], Darrah).
Regarding Claims 17, 10, and 3, SAP/Darrah discloses a system, wherein generating the set of predictive data sets utilizing a cluster based model comprises clustering search data associated with users' interaction with the data management system based on one or more dimensions ([0019], SAP; and [0047], Darrah).
Regarding Claims 18, 11, and 4, SAP/Darrah discloses a system, wherein the one or more data sets are ranked based on a likelihood weighting, and the selected ones of the set of predictive data sets are selected based on the likelihood weighting ([0049]-[0050], Darrah).
Regarding Claims 19, 12, and 5, SAP/Darrah discloses a system, wherein the likelihood weighting for each of the set of predictive data sets is based on a cluster size associated with that predictive data set ([0080] and [0090], Darrah).
Regarding Claims 20, 13, and 6, SAP/Darrah discloses a system, wherein generating the set of predictive data sets comprises generating a prompt for the LLM requesting predictive data sets, wherein the prompt includes search data associated with the users' interaction with the data management system ([0045], [0047] Darrah).
Regarding Claims 21, 14, and 7, SAP/Darrah discloses a system, wherein a set of predictive data sets includes a first set of predictive data sets generated from the cluster based model, and a second set of predictive data sets generated using the LLM, and wherein the selected ones of the set of predictive data sets are selected based on a likelihood weighting derived from an overlap between the first set of predictive data sets and the second set of predictive data sets ([0045], [0047] Darrah).
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 GIOVANNA B COLAN whose telephone number is (571)272-2752. The examiner can normally be reached Mon - Fri 8:30-5:00.
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/GIOVANNA B COLAN/Primary Examiner, Art Unit 2165 March 30, 2026