DETAILED ACTION
The following is a non-final, first office action in response to the amendment filed September 6, 2022. Claims 1-20 are currently pending and have been examined.
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 .
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 conflicting claims 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); 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 nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over (i) claims 1-20 of U.S. Patent Application No. 18/134,750. Although the claims at issue are not identical, they are not patentably distinct from each other because , see the comparison below for claim 1 of the instant Application, wherein all the underlined limitations of claim 1 are covered and anticipated by the highlighted limitations of claim 1 of the 18/134,750:
Claim 1 of the instant Application:
1. A method of measuring similarity for a sparsely populated dataset, the method comprising:
identifying fields in an initial dataset, the initial dataset including populated fields and null fields;
generating, by a computer device, a binary representation dataset that corresponds to the initial dataset by representing the populated fields of the initial dataset with a first binary value and representing the null fields of the initial dataset with a second binary value such that each of the fields in the initial dataset has a corresponding field in a corresponding position in the binary representation dataset, wherein the binary representation dataset is organized in rows and columns;
calculating a similarity measure for one or more pairs of rows of the binary representation dataset;
comparing, based on the similarity measure, each of the one or more pairs of rows of the binary representation dataset to a corresponding pair of rows in the initial dataset to identify similar pairs of rows in the initial dataset;
generating a recommendation based on the similar pairs of rows in the initial dataset; and
outputting the recommendation.
Claim 1 of 18/134,750:
1. A system for identifying similar items in an inventory, the system comprising:
an initial dataset formed of inventory data, the initial dataset including populated fields and null fields;
a user interface;
one or more processors; and computer-readable memory encoded with instructions that, when executed by the one or more processors, cause the system to:
identify fields in the initial dataset;
generate a binary representation dataset that corresponds to the initial dataset by representing the populated fields of the initial dataset with a first binary value and representing the null fields of the initial dataset with a second binary value such that each of the fields in the initial dataset has a corresponding field in a corresponding position in the binary representation dataset, the binary representation dataset being organized in rows and columns;
receive an input via the user interface, the input indicating a selection of an item in the inventory and corresponding to a row of interest in the binary representation dataset;
calculate a similarity measure for each pair of the row of interest and another row in the binary representation dataset;
compare, based on the similarity measure, each of the pairs in the binary representation dataset to a corresponding pair of rows in the initial dataset to identify similar pairs of rows in the initial dataset;
generate a recommendation of the similar items in the inventory based on the similar pairs of rows in the initial dataset; and
output the recommendation.
The limitations of the other independent claim 11 of the instant Application are similar and are covered and anticipated by the highlighted limitations of claim 1 of 18/134,750.
Examiner has reviewed the limitations of dependent claims 2-10 and 12-20 of the instant Application and they are covered and anticipated by the dependent claims 2-10 and 12-20 of 18/134,750.
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 a judicial exception (abstract idea) without significantly more.
Step 1: Statutory Category
(MPEP § 2106)
Claims 1-20 are directed towards a method and a system. The claims are directed to a statutory category: a process and an apparatus, as defined under 35 U.S.C. § 101.
Regarding Claim 1:
Step 2A, Prong One: Judicial Exception – Abstract Idea
(MPEP § 2106.04)
The claim recites an abstract idea, most reasonably a mathematical concept, because it includes steps of transforming data into a binary representation, calculating a similarity measure for pairs of rows, and comparing those results to identify similar pairs. USPTO guidance explains that mathematical formulas, calculations, and other mathematical relationships are abstract ideas under Step 2A, Prong One.
The limitations that compose the abstract idea are:
identifying fields in a dataset, including populated and null fields
generating a binary representation dataset by assigning one binary value to populated fields and another binary value to null fields
calculating a similarity measure for pairs of rows
comparing the similarity measure to corresponding rows in the initial dataset to identify similar pairs
generating a recommendation based on the similar pairs
These limitations amount to collecting and encoding data, mathematically evaluating similarity, and using the result to produce a recommendation. That is the kind of information analysis that generally falls within the abstract-idea grouping. Step 2A, Prong Two: Integration into a Practical Application
(MPEP § 2106.04(d))
The claim as written likely does not integrate the abstract idea into a practical application. USPTO guidance states that a claim is not “directed to” the exception only if additional elements apply the exception in a manner that imposes a meaningful limit, such as improving computer functionality, improving another technology, using a particular machine integral to the claim, or effecting a transformation of an article. Merely using a computer as a tool, or adding insignificant extra-solution activity, is not enough.
The additional elements here are minimal:
“by a computer device”
outputting the recommendation
Those extra elements do not recite any specific improvement to computer operation, database architecture, memory usage, network processing, or another technical field. The claim does not specify a particular similarity algorithm tied to a technical improvement, a specialized data structure that improves computer performance, or a concrete application beyond generating and outputting a recommendation. On this record, the computer appears to be invoked only as a tool to perform the abstract data analysis. Under USPTO guidance, that generally does not amount to integration into a practical application.
Step 2B: Inventive Concept
(MPEP § 2106.05)
The claim also fails Step 2B as currently drafted. USPTO guidance explains that if the additional elements beyond the abstract idea are only generic computer implementation or insignificant post-solution activity, they do not amount to “significantly more.”
Here, the extra elements appear to be:
generic use of a “computer device”
output of the recommendation
Nothing in the claim indicates that these elements are anything other than routine computer functions. The heart of the claim remains the abstract data manipulation and similarity analysis itself. Absent additional claim language tying the process to a specific technical improvement or other meaningful limitation, there is likely no inventive concept.
Therefore, the claim is not directed to patent-eligible subject matter under 35 U.S.C. § 101.
Regarding Claim 11
Independent Claim 10 is parallel in scope to claim 1 and ineligible for similar reasons.
Regarding Claims 2-11 and 12-20
Dependent claims 2-11 and 12-20 merely set forth further embellishments to the abstract idea (i.e., they serve to further limit practically performable determining and associating functions), and therefore do not confer eligibility on the claimed invention and are ineligible for similar reasons to claims 1 and 11.
Claim Rejections - 35 USC § 102
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.
Claims 1-4, 9-14, 19, and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Bucak et al (US 2012/0030020 A1).
Regarding claims 1 and 11, Bucak discloses a method of measuring similarity for a sparsely populated dataset, the method comprising:
identifying fields in an initial dataset, the initial dataset including populated fields and null fields; generating, by a computer device, a binary representation dataset that corresponds to the initial dataset by representing the populated fields of the initial dataset with a first binary value and representing the null fields of the initial dataset with a second binary value such that each of the fields in the initial dataset has a corresponding field in a corresponding position in the binary representation dataset, wherein the binary representation dataset is organized in rows and columns; (Bucak: Figure 1, paragraph [0030] - At step 100 in FIG. 1, the computing system applies a weighted non-negative matrix factorization (NMF) on the client-product matrix X, and simultaneously or sequentially optimizes zero-valued elements in the matrix X that correspond to unknown client-product affinities, paragraph [0033] - At step 110, based on the matrices W and H and/or the optimization performed at step 100, the matrix X is reconstructed as a prediction matrix {circumflex over (X)}=WH);
calculating a similarity measure for one or more pairs of rows of the binary representation dataset; comparing, based on the similarity measure, each of the one or more pairs of rows of the binary representation dataset to a corresponding pair of rows in the initial dataset to identify similar pairs of rows in the initial dataset; (Bucak: Figure 1, paragraph [0038] - Returning to FIG. 1, at step 120, the computing system identifies at least one client-product pair with the highest value elements in the matrix {circumflex over (X)}.);
generating a recommendation based on the similar pairs of rows in the initial dataset; and outputting the recommendation (Bucak: Figure 1, paragraph [0038] - At step 130, the computing system recommends at least one product to at least one client according to the client-product pair with the highest value.).
Regarding claims 2 and 12, Bucak discloses all of the limitations as noted above in claims 1 and 11. Bucak further discloses wherein the initial dataset and the binary representation dataset have same dimensions; and wherein each of the fields in the initial dataset has one and only one corresponding field in the binary representation dataset (Bucak: paragraph [0039] - For example, the computing system maps rows or columns of the matrix X that correspond to clients into the matrix W. Similarly, the computing system maps rows or columns of the matrix X that correspond to products into the matrix H.).
Regarding claims 3 and 13, Bucak discloses all of the limitations as noted above in claims 1 and 11. Bucak further discloses wherein generating the binary representation dataset further comprises maintaining a key column from the initial dataset in the binary representation dataset to identify each of the rows of the binary representation dataset (Bucak: Figure 4).
Regarding claims 4 and 14, Bucak discloses all of the limitations as noted above in claims 1 and 11. Bucak further discloses wherein the populated fields in the initial dataset are populated with numerical values, textual values, or a combination of numerical and textual values (Bucak: Figure 4, paragraph [0057] - The dataset consists of 100,000 ratings on an integer scale from 1 to 5 given to 1642 movies by 943 users.).
Regarding claims 9 and 19, Bucak discloses all of the limitations as noted above in claims 1 and 11. Bucak further discloses wherein the initial dataset includes one or more null fields in one or more rows of the initial dataset (Bucak: Figure 4).
Regarding claims 10 and 20, Bucak discloses all of the limitations as noted above in claims 1 and 11. Bucak further discloses wherein the initial dataset includes one or more null fields in each row of the initial dataset (Bucak: Figure 4).
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.
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(a) 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 5-8 and 15-18 are rejected under 35 U.S.C. 103 as being unpatentable over Bucak et al (US 2012/0030020 A1) in view of Linden et al (US 6,266,649 B1).
Regarding claims 5 and 15, Bucak discloses all of the limitations as noted above in claims 1 and 11. Bucak does not expressly disclose refining the similarity measure into a composite similarity score before generating the recommendation; wherein generating the recommendation further includes generating the recommendation based on the composite similarity score. Linden discloses refining the similarity measure into a composite similarity score before generating the recommendation; wherein generating the recommendation further includes generating the recommendation based on the composite similarity score (Linden: column 15 lines 27-35 - In step 186, the weighted similar items lists are merged (if multiple lists exist) to form a single list. During this step, the scores of like items are summed. For example, if a given other item appears in three different similar items lists 64, the three scores (including any negative scores) are summed to produce a composite score, Figure 5 - recommend items 194).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and apparatus of Bucak to have included refining the similarity measure into a composite similarity score before generating the recommendation; wherein generating the recommendation further includes generating the recommendation based on the composite similarity score, as taught by Linden because it would reflect the current preferences of the user (Linden: column 1).
Regarding claims 6 and 16, Bucak and Linden teach or suggest all the limitations of claims 5 and 15 as noted above. Bucak further discloses wherein refining the similarity measure further includes modifying the weight of one or more attributes of the initial dataset in the similarity measure (Bucak: paragraph [0030] - Since the computing system does not know the exact interpretation of the zero-valued elements in the matrix X whereas one-valued elements definitely mean that corresponding clients are interested in corresponding products by buying them, the computing system may give more weight (larger C.sub.ij) to positive entries so that the factorization will be compatible with the positive entries).
Regarding claims 7 and 17, Bucak and Linden teach or suggest all the limitations of claims 5 and 15 as noted above. Linden further discloses wherein refining the similarity measure further includes excluding the similarity measure for one or more pairs of rows of the binary representation dataset (Linden: column 15 lines 40-50 - In step 192 one or more items are optionally selected from the recent shopping cart contents list (if such a list exists) for the user, excluding items that have been rated by the user or which fall outside the designated product group or category).
Regarding claims 8 and 18, Bucak discloses all of the limitations as noted above in claims 1 and 11. Bucak does not expressly disclose wherein the initial dataset is a combined dataset that includes data from multiple data sources; and wherein the data from the multiple data sources includes multiple standardized data structures having one or more non-overlapping attributes. Linden discloses wherein the initial dataset is a combined dataset that includes data from multiple data sources; and wherein the data from the multiple data sources includes multiple standardized data structures having one or more non-overlapping attributes (Linden: Figure 2 - combine similar item lists 86).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the method and apparatus of Bucak to have included wherein the initial dataset is a combined dataset that includes data from multiple data sources; and wherein the data from the multiple data sources includes multiple standardized data structures having one or more non-overlapping attributes, as taught by Linden because it would reflect the current preferences of the user (Linden: column 1).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
PTO-892 Reference U discloses Item-based collaborative filtering recommendation algorithm.
PTO-892 Reference V discloses Data mining by means of binary representation: a model for similarity and clustering.
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KATHLEEN GAGE PALAVECINO
Primary Examiner
Art Unit 3688
/KATHLEEN PALAVECINO/Primary Examiner, Art Unit 3688
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