DETAILED ACTION
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 § 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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claimed invention is directed to one or more abstract ideas without significantly more. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than judicial exception. The eligibility analysis in support of these findings is provided below.
Step 1:
The claimed method (claims 1-7), computer program product (claims 8-13), and system (claims 14-20) are directed to one of the eligible categories of subject matter and therefore satisfies step 1.
Step 2A, Prong One:
Independent claim 1 (8 and 14) recites the following limitations that can be practically performed in the mind and/or with a pen and a piece of paper:
absorbing profiles of the time series data and anomaly types of a model as features;
optimizing biased ranks to create optimized ranks through merging initial ranks with new ranks generated by real anomalies; and
suggesting the optimized ranks.
Step 2A, Prong Two:
The additional elements are:
auto-suggesting for saving a predetermined amount of data operations.
These additional elements are using generic computer functions as a tool to perform.
Step 2B:
For Step 2B, the additional elements, taken individually and in combination, do not result in the claim, as a whole, amounting to significantly more than the identified judicial exception. MPEP 2106.07(a)(III)(B) identifies the list of cases in MPEP 2106. 05(d)(II) as available bases. Taking these aforementioned additional elements as an ordered combination, these additional elements add nothing that is not already present when the elements are considered separately.
As per dependent claims:
Step 2A, Prong One:
Claim 2 (9 and 15): based on the time series data, the initial ranks of the model are generated during the absorbing.
Claim 3 (10 and 16): wherein the profiles include profiling the time series data of the model and the anomaly types by generating synthesized anomaly data.
Claim 4 (11 and 17): during the optimizing, a relationship between the generated initial ranks and the profiled time series data of the model is stored.
Claim 5 (12 and 18): wherein the optimized ranks are utilized for selecting top N models, where N is an integer.
Claim 6 (13 and 19): wherein a value of N is set by a user.
The above identified limitations can be practically performed in the mind and/or with a pen and a piece of paper.
As per dependent claims:
Step 2A, Prong Two:
Claim 7 ( 20): embodied in a cloud-computing environment.
The additional elements of dependent claims are directed to generic computer functions.
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 (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 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.
Claims 1-20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Heikkila (FI 20205605 A1) in view of Adjaoute (US Pub. 2018/0053114).
Regarding claim 1, Heikkila discloses a computer-implemented time series anomaly detection method that processes time series data, the method comprising:
absorbing [profiles of] the time series data and anomaly types of a model as features (p. 6, lines 14-22, a prediction model is developed for time series data and prediction error of the model is monitored);
optimizing biased ranks to create optimized ranks through merging initial ranks with new ranks generated by real anomalies (p. 16, lines 10-23, The results of the expert evaluation are used as follows: a. Labels (anomaly confirmed/rejected) given by expert are analyzed. b. Variables of the target system are given scores indicating how often they tend to be involved in positively confirmed anomalies); and
auto-suggesting the optimized ranks for saving a predetermined amount of data operations (p. 16, lines 10-23).
While Heikkila discloses type of time series data but does not explicitly profiles [of time series data], Adjaoute discloses profiles of time series data (¶ [0142], Transactions, and therefore profiles normally have dozens of datapoints that either come directly from each transaction or that are computed from transactions for a single entity over a series of time intervals).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Adjaoute into Heikkila to account for velocity count expansions of the data point values when analyzing the transaction vulnerability.
Regarding claim 2, Heikkila in view of Adjaoute discloses the computer-implemented time series anomaly detection method of claim 1, wherein, based on the time series data, the initial ranks of the model are generated during the absorbing (Adjaoute, ¶ [0074], initialize a population of elements where each element represents one possible set of initial attributes).
Regarding claim 3, Heikkila in view of Adjaoute discloses the computer-implemented time series anomaly detection method of claim 1, wherein the profiles include profiling the time series data of the model and the anomaly types by generating synthesized anomaly data (A, ¶ [0050]).
Regarding claim 4, Heikkila in view of Adjaoute discloses the computer-implemented time series anomaly detection method of claim 1, wherein, during the optimizing, a relationship between the generated initial ranks and the profiled time series data of the model is stored (A, ¶ [0236], relationship of data and models).
Regarding claim 5, Heikkila in view of Adjaoute discloses the computer-implemented time series anomaly detection method of claim 1, wherein the optimized ranks are utilized for selecting top N models, where N is an integer (A, ¶ [0069], Table 1).
Regarding claim 6, Heikkila in view of Adjaoute discloses the computer-implemented time series anomaly detection method of claim 5, wherein a value of N is set by a user (A, ¶ [0069], Table 1).
Regarding claim 7, Heikkila in view of Adjaoute discloses the computer-implemented time series anomaly detection method of claim 1, embodied in a cloud-computing environment (it’s readily available – e.g. Zeng’s disclosure below).
Regarding claims 8-13, see discussion of claims 1-6 for the same reason of rejection.
Regarding claims 14-20, see discussion of claims 1-7 for the same reason of rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Zeng discloses a system for outdoor target tracking. US Pub. 2020/0182995.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TUANKHANH D PHAN whose telephone number is (571)270-3047. The examiner can normally be reached on Mon-Fri, 10:00am-18:00pm.
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, Boris Gorney can be reached on 571-270-5626. 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 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 or 571-272-1000.
/TUANKHANH D PHAN/ Examiner, Art Unit 2154