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 .
Information Disclosure Statement
The information disclosure statements (IDS) were submitted on 01/30/2023 and 06/28/2023. The submissions are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: 140A in Figure 1. Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they do not include the following reference sign(s) mentioned in the description: 650 in Figure 6. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Objections
Claims 2, 12, and 20 are objected to because of the following informalities:
Claims 2 and 12 detail “extracting, by the data preprocessor..” which should read “extracting, by a data preprocessor” as this is the first mention of “data preprocessor” and the correct antecedent basis is “a” rather than “the”.
Claim 20 Lines 3-4 detail “one or more hardware processors for running the program code to jointly encode…”. The claim limitation should include a colon after code so that it reads “one or more hardware processors for running the program code to: jointly encode..”.
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 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.
The term “top relevant” in claims 1, 11, and 20 is a relative term which renders the claim indefinite. The term “top relevant” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is not clear nor distinct which multivariate time series segments are considered to be “top relevant multivariate time series segments” as the claims nor the specifications provides a standard to determine the requisite degree that a multivariate time series segment is “top relevant”.
Examiner interprets the limitation as multivariate time series segment that is different from the trend of multivariate time series segments.
Claims 2-10 are rejected due to dependence on Claim 1. Claims 12-19 are rejected due to dependence on Claim 11.
Claims 2-6 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.
Claim 1 details “jointly encoding, by a dual-channel feature extractor, a current time series segment with corresponding static statuses into a compact feature.”
Claim 2, which is dependent on Claim 1, details the limitations:
jointly encoding, by a dual-channel feature extractor, the multivariate time series segments and the corresponding static statuses into compact features having a certain dimension which is much smaller than a multiplication of an original dimension and a length of the multivariate time series segments;
updating network parameters of the dual-channel feature extractor based on results of the evaluation to reduce a loss of a loss function based on stochastic gradient descent
It is not clear nor distinct whether the “dual-channel feature extractor” as detailed in Claim 2 (a) is the same or different from the “dual-channel feature extract” or Claim 1. Furthermore, the second mention in Claim 2 of “the dual-channel feature extractor” is unclear whether it is in reference to the “dual-channel feature extractor” of Claim 1 or Claim 2.
Examiner interprets the “dual-channel feature extractor” of Claim 2 to be the same “dual-channel feature extractor” of Claim 1.
Claims 3-6 are rejected due to dependence on Claim 2.
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. The claimed invention is directed to the abstract concept of performing abstract steps without significantly more. The claim(s) recite(s) the following abstract concepts in BOLD of
1. A computer implemented method, comprising:
jointly encoding, by a dual-channel feature extractor, a current time series segment with corresponding static statuses into a compact feature;
converting, by a binary code extractor, the compact feature into a binary code;
computing distances between the binary code and all binary codes stored in a binary code database; and
retrieving the top relevant multivariate time series segments based on the distances.
11. A computer program product, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising:
jointly encoding, by a dual-channel feature extractor implemented by one or more hardware processors of the computer, a current time series segment with corresponding static statuses into a compact feature;
converting, by a binary code extractor implemented by the one or more hardware processors, the compact feature into a binary code;
computing, by the one or more hardware processors, distances between the binary code and all binary codes stored in a binary code database; and
retrieving, by the one or more hardware processors, the top relevant multivariate time series segments based on the distances.
20. A computer processing system, comprising:
a memory device for storing program code; and
one or more hardware processors for running the program code to
jointly encode, by a dual-channel feature extractor implemented by the one or more hardware processors, a current time series segment with corresponding static statuses into a compact feature;
convert, by a binary code extractor implemented by the one or more hardware processors, the compact feature into a binary code;
compute distances between the binary code and all binary codes stored in a binary code database; and
retrieve the top relevant multivariate time series segments based on the distances.
Under step 1 of the eligibility analysis, we determine whether the claims are to a statutory category by considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. The above claims are considered to be in a statutory category.
Under Step 2A, Prong One, we consider whether the claim recites a judicial exception (abstract idea). In the above claim, the highlighted portion constitutes an abstract idea because, under a broadest reasonable interpretation, it recites limitation the fall into/recite abstract idea exceptions. Specifically, under the 2019 Revised Patent Subject Matter Eligibility Guidance, it falls into the grouping of subject matter that, when recited as such in a claim limitation, covers performing mathematics or mental steps.
Next, under Step 2A, Prong Two, we consider whether the claim that recites a judicial exception is integrated into a practical application. In this step, we evaluate whether the claim recites additional elements that integrate the exception into a practical application of that exception.
This judicial exception is not integrated into a practical application because there is no improvement to another technology or technical field; improvements to the functioning of the computer itself; a particular machine; effecting a transformation or reduction of a particular article to a different state or thing. Examiner notes that since the claimed methods and system are not tied to a particular machine or apparatus, they do not represent an improvement to another technology or technical field. Similarly there are no other meaningful limitations linking the use to a particular technological environment. Finally, there is nothing in the claims that indicates an improvement to the functioning of the computer itself or transform a particular article to a new state.
Finally, under Step 2B, we consider whether the additional elements are sufficient to amount to significantly more than the abstract idea. Claim 1 contain no additional elements. Claims 11 and 20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because a hardware processor of a computer, memory devices, and a computer are interpreted under broadest reasonable interpretation to be a generic computer elements. Generic computer elements are not considered significantly more than the abstract idea and do not integrate the abstract idea into a practical application. As recited in the MPEP, 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94.
The additional element of Claims 2 and 12 to extract multivariate time series segments and corresponding statis statuses from historical data are considered necessary data gathering. As recited in MPEP section 2106.05(g), necessary data gathering (i.e. extracting data) is considered extra solution activity in light of Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015).
The data preprocessor of Claims 2 and 12 are interpreted under broadest reasonable interpretation to be a generic computer element. Generic computer elements are not considered significantly more than the abstract idea and do not integrate the abstract idea into a practical application. As recited in the MPEP, 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94.
The additional element of the storing of binary codes in a binary code data base of Claims 3 and 13 are interpreted to be a generic function performed on a generic computer. As recited in the MPEP, 2106.05(b), merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. 2347, 2359-60, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94.
Claims 2-10 and 12-19 further limit the abstract ideas without integrating the abstract concept into a practical application or including additional limitations that can be considered significantly more than the abstract idea.
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, 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, 11, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Song (US20190034497) in view of Lee (US20150012274) and Eck (US8880415).
As best understood, in regards to Claims 1, 11, and 20, Song teaches “a memory device for storing program code (memory – [0083]); and
one or more hardware processors for running the program code (processor – [0083]) to
encoding, by a feature extractor, a current time series segment into a compact feature (feature extraction is conducted by an input attention based LSTM/GRU algorithm to obtain a fixed size feature vector for each time series segment – [0025], Figure 1; encoding step 108 – Figure 1);
converting, by a binary code extractor, the compact feature into a binary code (binary code generation – [0029], Figure 1);
computing distances (“The pairwise loss produces similar hash codes for similar pairs and produces dissimilar hash codes for dissimilar pairs. Meanwhile, the triplet loss (e.g., anchor, positive, negative) can be employed to ensure that a Hamming distance between anchor and positive is less than a Hamming distance between anchor and negative” – [0018]);
retrieving the top relevant multivariate time series segments based on the distances (“A non-transitory computer-readable storage medium comprising a computer-readable program is presented for employing deep learning for time series representation and retrieval, wherein the computer-readable program when executed on a computer causes the computer to perform the steps of retrieving multivariate time series segments from a plurality of sensors, storing the multivariate time series segments in a multivariate time series database constructed by a sliding window over a raw time series of data, applying an input attention based recurrent neural network to extract real value features and corresponding hash codes, executing similarity measurements by an objective function, given a query, obtaining a relevant time series segment, i.e. top relevant, from the multivariate time series segments retrieved from the plurality of sensors” – [0006]).”
Song is silent with regards to the language of “jointly encode, by a dual-channel feature extractor, a segment with corresponding static statuses into a compact feature.”
Lee teaches “jointly encoding, by a dual-channel feature extractor, a segment with corresponding static statuses into a compact feature (static feature extracting portion, i.e. static status, with dynamic feature extracting portion, i.e. segment, with the combining of the static feature and the dynamic feature, i.e. compact feature – [0032])”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Song to incorporate the teaching of Lee to combine the static features and the dynamic features. By utilizing the static features and the dynamic features in conjunction this yields an improved feature vector being generated and the analysis to be performed upon the feature vector.
Song in view of Lee are silent with regards to the language of “computing distances between the binary code and all binary codes stored in a binary code database.”
Eck teaches “computing distances between the binary code and all binary codes stored in a binary code database (“The WTA hash is a sparse embedding method that transforms the input feature space into binary codes such that Hamming distance in the resulting space closely correlates with rank similarity measures. In vector analysis, precise values of each feature dimension (e.g., values in X[t]) are often not important. The WTA algorithm transforms the vector representations (e.g., X[t]) to identify which values in the representations are higher and which ones are lower to create a ranking over these values. The input for the WTA algorithm is set of μ permutations Θ, window size K, input vector X. The output of the WTA algorithm is sparse vector codes CX .” – Column 9 Lines 15-50).”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Song in view of Lee to incorporate the teaching of Eck to utilize a WTA hash to transform the input feature into binary codes so that the Hamming distance can be utilized to determine similarities. By utilizing the WTA hash to transform the input feature into binary codes and performing Hamming distance determinations this is an improvement that improves the quality of the evaluation of time series based systems.
Examiner’s Note
Claims 2-10 and 12-19 are not rejected under a prior art rejection (35 U.S.C. 102 or 35 U.S.C. 103).
In regards to Claims 2 and 12, Song in view of Lee and Eck discloses the claimed invention as detailed in claims 1 and 11. Song further teaches “extracting, by the data preprocessor, multivariate time series segments and corresponding static statuses from historical data (“multivariate time series segment query, the Data2Data engine or module can automatically generate relevant real value features as well as hash codes of the query and return the most relevant time series segments in the historical data” – [0019]);
Song in view of Lee and Eck are silent with regards to the language of “jointly encoding, by a dual-channel feature extractor, the multivariate time series segments and the corresponding static statuses into compact features having a certain dimension which is much smaller than a multiplication of an original dimension and a length of the multivariate time series segments;
performing an evaluation of the encoded compact features by supervised metric learning loss to provide compact features that preserve a local similarity of multivariate time series segments and the corresponding static statuses in an input space;
updating network parameters of the dual-channel feature extractor based on results of the evaluation to reduce a loss of a loss function based on stochastic gradient descent; and
repeating said jointly encoding, evaluating, and updating steps until a stopping condition is reached to provide a trained dual-channel feature extractor.”
Claims 3-6 are dependent on Claim 2 and Claims 13-16 are dependent on Claim 12.
In regards to Claims 7 and 17, Song in view of Lee and Eck discloses the claimed invention as detailed in Claims 1 and 11. Song further teaches “the dual-channel feature extractor comprises a multi-layer perceptron and a recurrent neural network (“Regarding FIGS. 1 and 2, a recurrent neural network is employed. A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed graph along a sequence. This allows RNNs to exhibit dynamic temporal behavior for a time sequence. Unlike feedforward neural networks, RNNs can use their internal state (memory) to process sequences of inputs. Recurrent neural networks are used somewhat indiscriminately about two broad classes of networks with a similar general structure, where one is finite impulse and the other is infinite impulse. Both classes of networks exhibit temporal dynamic behavior. A finite impulse recurrent network is a directed acyclic graph that can be unrolled and replaced with a strictly feedforward neural network, while an infinite impulse recurrent network is a directed cyclic graph that cannot be unrolled” – [0039]; “Gated recurrent units (GRUs) are a gating mechanism in recurrent neural networks” – [0042]; with the input time series XK, an input attention mechanism 144 can be constructed via a deterministic attention model, e.g. a multilayer perception, by referring to the previous hidden state and the cell states in the encoder LSTM/GRU unit – [0051]; Figure 3 shows the input attention mechanism 144 with the encoder LSTM/GRU unit).”
Song in view of Lee and Eck are silent with regards to the language of “the dual-channel feature extractor comprises a multi-layer perceptron and a recurrent neural network whose respective outputs are combined by a combining element into a binary prediction layer”.
Claims 8-10 are dependent on Claim 7 and Claims 18-19 are dependent on Claim 17.
Conclusion
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/YOSSEF KORANG-BEHESHTI/Examiner, Art Unit 2863