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 Amendment
This Office action has been issued in response to amendment filed on 01/16/2026, Claims (1-7), (8-14) and (15-21) are pending. Applicants' arguments have been carefully and respectfully considered and addressed. Accordingly, this action has been made FINAL necessitated by amendment.
Claims (1-7), (8-14) and (15-21) are presented for examination.
Response to Arguments
Applicants' arguments have been carefully and respectfully considered and addressed. The arguments presented are moot based on amendment.
Applicant arguments and amendment were fully considered and are moot in view of the new ground rejection wherein Chari et al. US Patent Application Publication US 20170061322 A1 (hereinafter Chari) in view of Qin et al. US Patent Application Publication US 20180032563 A1 (hereinafter Qin) and further in view of Cote et al. US Patent Application Publication US 20180248905 A1 (hereinafter Cote) for teaching the amended claims.
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 claims at issue 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); and 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 a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claims 1, 8 and 15 are rejected on the ground of nonstatutory double patenting over claims 1, 13 and 18 of copending Application No. 11449786 since the subject matter claimed in the claims 1, 8 and 15 of the instant application is directed to the same common subject matter in the claims 1, 13 and 18 of U.S. Patent copending Application No. 11449786.
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 of this title, 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 1-21 are rejected under AIA 35 U.S.C. 103(a) as being unpatentable over Chari et al. US Patent Application Publication US 20170061322 A1 (hereinafter Chari) in view of Qin et al. US Patent Application Publication US 20180032563 A1 (hereinafter Qin) and further in view of Cote et al. US Patent Application Publication US 20180248905 A1 (hereinafter Cote).
Regarding claim 1, Chari teaches Amended) At least one [[A]] non-transitory computer-readable storage medium comprising instructions that (Claims 10-11 text), when executed, cause a machine to at least: obtain a user definition of a function to generate a normal data series (Abstract, Claim 12 text, wherein Chari stores a series of machine-learning instructions to execute a method of generating a normal sample data set and an abnormal (anomalous) sample data set to serve as a classifier for training a model for an anomalous detection monitor for a target user).
Chari does not teach determine a timeline of data based on the function; determine a time scale associated with anomaly generation; add anomaly data to the timeline of data based on the time scale; cause storage of the timeline as an anomaly detection dataset with the anomaly data in a data map including timestamps associated with the anomaly data.
However in analogous art of detecting anomaly, Qin teaches determine a timeline of data based on the function (Abstract, [0042-0043], Claims 1, 15 text, wherein Qin provides means for determining time frame or time interval for anomaly data) determine a time scale associated with anomaly generation; add anomaly data to the timeline of data based on the time scale (FIGS. 2-8, Abstract, [0042-0049] Claims 1, 15 text, wherein Qin displays the anomaly on the time scale based on timestamps and time frame) cause storage of the timeline as an anomaly detection dataset with the anomaly data in a data map including timestamps associated with the anomaly data (FIGS. 2-8, Abstract, [0042-0049], [0057], Claims 1, 15 text, wherein Qin stores data uses anomaly data as plotting and creates a graph for mapping the anomaly data with timestamps on the graph).
It would have been obvious to a person in the ordinary skill in the art before the effective filing date of the claimed invention to combine Chari with Qin by incorporating the method of determine a timeline of data based on the function; determine a time scale associated with anomaly generation; add anomaly data to the timeline of data based on the time scale; cause storage of the timeline as an anomaly detection dataset with the anomaly data in a data map including timestamps associated with the anomaly data of Qin into the method of obtain a user definition of a function to generate a normal data series of Chari for the purpose of graphically displaying data and allow users to analyze the polled data that can be normal or anomaly data. (Qin: [0018-0019]).
Chari does not teach train a machine learning classifier utilizing the anomaly detection dataset.
However in analogous art of detecting anomaly, Cote teaches train a machine learning classifier utilizing the anomaly detection dataset ([0047] wherein Cote describes leveraging dataset by a machine learning algorithm to build classifiers and train it to recognize the normal/abnormal behavior, wherein the machine learning is part of an anomaly detection system).
It would have been obvious to a person in the ordinary skill in the art before the effective filing date of the claimed invention to combine Chari with Cote by incorporating the method of train a machine learning classifier utilizing the anomaly detection dataset of Cote into the method of obtain a user definition of a function to generate a normal data series of Chari for the purpose of labeling data before training of detecting the difference between normal and anomalous data, wherein the training can utilize the labeled data and supervised learning to build one or more classifiers to recognize the anomaly. (Cote: [0005]).
Regarding claim 2, Chari as modified by Qin and Cote teaches wherein the machine learning classifier is a deep-learned-based classifier ([0047] wherein Cote incorporates deep neural network for the machine learning).
Regarding claim 3, Chari as modified by Qin and Cote teaches wherein the instructions, when executed, cause the machine to generate random anomaly data (Abstract, claim 12 texts, wherein Chari stores a series of machine-learning instructions to execute a method of generating a normal sample data set and an abnormal (anomalous) sample data set to serve as a classifier for training a model for an anomalous detection monitor for a target user).
Regarding claim 4, Chari as modified by Qin and Cote teaches wherein adding the anomaly data is based on an anomaly probability parameter ([0006], [0026], [0074], [0090-0095] wherein Cote provides a single probability output of the anomaly based on the live PM data. The PM data cam ne representative of a normally functioning network such that the single probability output provides an indication of a departure from the normally functioning network. The single probability output can be a p-value from multiple different PM types. The training can build a set of Probability Density Functions (PDFs) from the PM data, builds a likelihood function for each PDF, and builds a global likelihood function based on a product of each individual likelihood function, and wherein the global likelihood function can be a single multivariate function to describe a network component. The global likelihood function can be used to calculate a p-value and the anomaly is detected based on the p-value.
Regarding claim 5, Chari as modified by Qin and Cote teaches wherein the instructions, when executed, cause the machine to generate anomaly data based on a user-defined function ([0012], [0035], [0057], [0069], [0084] wherein Chari generates anomaly data based the target user).
Regarding claim 6, Chari as modified by Qin and Cote teaches wherein the anomaly data and the normal data include respective data slices, wherein the instructions, when executed, cause the machine to splice the data slices together to combine the anomaly data with the normal data ([0020], [0026], [0064] wherein Qin merges the anomaly data with the normal data).
Regarding claim 7, Chari as modified by Qin and Cote teaches wherein the user definition of the function includes an executable file ([0031], [0038-0039] wherein Cote incorporates a software for anomalous data with machine learning parameters that can be adjusted by users).
Regarding claim 8, Chari teaches an apparatus comprising: memory; computer executable instructions; programmable circuitry to execute the computer executable instructions (Abstract, [0125-0127]). Claim 8 is similar in scope to claim 1 therefore the claim is rejected under similar rationale.
Claim 9 is similar in scope to claim 2 therefore the claim is rejected under similar rationale.
Claim 10 is similar in scope to claim 3 therefore the claim is rejected under similar rationale.
Claim 11 is similar in scope to claim 4 therefore the claim is rejected under similar rationale.
Claim 12 is similar in scope to claim 5 therefore the claim is rejected under similar rationale.
Claim 13 is similar in scope to claim 6 therefore the claim is rejected under similar rationale.
Claim 14 is similar in scope to claim 7 therefore the claim is rejected under similar rationale.
Regarding claim 15, Claim 15 is similar in scope to claim 1 therefore the claim is rejected under similar rationale.
Claim 16 is similar in scope to claim 2 therefore the claim is rejected under similar rationale.
Claim 17 is similar in scope to claim 3 therefore the claim is rejected under similar rationale.
Claim 18 is similar in scope to claim 4 therefore the claim is rejected under similar rationale.
Claim 19 is similar in scope to claim 5 therefore the claim is rejected under similar rationale.
Claim 20 is similar in scope to claim 6 therefore the claim is rejected under similar rationale.
Claim 21 is similar in scope to claim 7 therefore the claim is rejected under similar rationale.
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.
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/HASSAN MRABI/Examiner, Art Unit 2144