Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
2. Claims 1-20 were previously pending. In this Response, claims 1, 3, 5, 8-12, 14, 16, and 18-20 are amended. Claim 7 is canceled. No claims are newly added. As such, claims 1-6 and 8-20 remain pending and under consideration.
3. This office action is in response to the RCE filed 01/28/2026.
4. Claims 1 and 14 are independent claims.
5. The office action is made non-final.
Double Patenting
6. Applicant respectfully requests that this rejection be held in abeyance until the claims are otherwise considered allowable, as the scope of the claims may change during prosecution such that a double patenting rejection is not appropriate.
Therefore, the Double patenting rejection is still in effect.
Examiner Note
7. The Examiner cites particular columns and line numbers in the references as applied to the claims below for the convenience of the Applicant(s). Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the Applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Claim Rejections - 35 USC § 102
8. 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.
9. 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;
10. Claims 1-6 and 8-20 are rejected under 35 U.S.C. 102(a) (1) as being anticipated by Gollapudi et al (US 20110145226 A1) hereinafter as Gollapudi.
11. Regarding claim 1, Gollapudi teaches A method for generating and using a text-based search term, the method comprising:
Examiner notes and interpretations: In technical, content management, and data analysis contexts, source attributes and tags differ primarily in their structure, specificity, and purpose. Generally, attributes provide detailed, specific, and structured metadata (e.g., size, color, author) about a source item, while tags are loose, unstructured labels used for broad classification or grouping.
Definition & Structure:
Source Attributes: Defined as name-value pairs, providing detailed characteristics of an item (e.g., color="blue", width="100px").
Tags: Simple, often unstructured, labels used to categorize items (e.g., "urgent", "Q1-report", "social-media").
extracting at least two attributes of a source item from source item information item ([0006], “Each product may have one or more attributes (at least two attributes).”, [0008], “A plurality of products (and/or services) responsive to the query is identified by the computer device. Each product has one or more attributes.”, [0026], “the attributes may be extracted by a module or application that is trained to extract relevant attributes from a webpage… attributes such as the model’s name, product type, product color, and brand name may be extracted. Other types of attributes may also be extracted.”, [0021], “product descriptions”), the extracting comprising identifying at least two tags in the source item information, wherein the at least two tags are associated with the at least two attributes of the source ([0025], “the history data 155 (at least two tags) may be classified by genre or category… search sessions (at least two tags) that ended in webpages associated with electronics may be categorized as electronics related.”, [0026], “the history data 155 ((at least two tags)) may be further associated with one or more attributes. Where the history data 155 comprises webpage identifiers (e.g., URLs), the attributes may be based on words extracted from the text or title of the identified webpages”);
generating a search term comprising the at least two tags, wherein the search term comprises the at least two attributes ([0008], “A query may be received by a computer device through a network. The query includes one or more attributes (at least two attributes). A plurality of products (and/or services) responsive to the query is identified by the computer device. Each product has one or more attributes.”, [0023], “the attributes may correspond to the terms of the queries. Thus, the query "Sony Television" may be associated with the attributes "Sony" and "Television". the attributes may be based on the terms but may not exactly correspond to the terms of the query.”, [0031-0032], “the importance score may be a numerical score where a higher importance score evidences high importance and a lower importance score evidences low importance (tags with different importance score). An attribute with a high importance score (tag) (e.g., as compared with a threshold, e.g., determined by a user or an administrator) may not be substituted with another attribute or removed from the attributes of a query.”, [0033], “The distance engine 140 may further recommend or generate similar queries from a received query using the terms of the queries as attributes and the similarity data 135 and the importance data 125.”);
using the search term to search for competitor item information in at least two successive queries, wherein, in each successive query, a lowest priority tag of the at least two tags is sequentially dropped off from the search term (Fig 3, [0030], “the distance engine 140 may use the attribute frequency data 145 to determine the similarities of attribute pairs, as well as a relative importance of an attribute. A determined similarity score of an attribute pair and an importance score of an attribute may then be applied to attributes of a query.”, [0031-0032], “For example, in the query "Sony pink digital camera", the attribute "pink" may have a low importance score (a lowest priority tag) and a high similarity score with the attribute "purple". This may indicate that the attribute "pink" may be removed from the query or substituted with "purple".”, [0045], “the distance engine 140 may substitute one or more attributes of a query with one or more alternate attributes based on the similarity and importance data.”, [0054], “The similarity score may be used to determine the substitutability of an attribute for another attribute. For example, an attribute with a low similarity score with respect to another attribute may not be substitutable with each other, whereas attributes with a high similarity score may essentially be synonyms for one another.”); and
computing a similarity score between the source item information and the competitor item information from the at least two successive queries ([0006], Fig 1, [0018], “determining attribute frequencies and recommending products based on user queries.”, [0033], “generate a product distance score which is a measure of the distance between two products based on the attributes associated with the products and the similarity data 135. The distance engine 140 may further recommend or generate similar queries from a received query using the terms of the queries as attributes and the similarity data 135 and the importance data 125.”, [0043], “compute the similarity of two products by computing the sum of the similarity scores for each attribute i of the first product with each attribute j of the second product.”), wherein computing the similarity score comprises:
generating a first value pair for the source item and a first competitor item, and for the first value pair: assigning a first value to a degree of similarity between the source item and the first competitor item with respect to a first common feature ([0005], “For each of a plurality of unique attribute pairs, a similarity score may be determined for the pair using the correlation.”, [0030], “The similarity score of an attribute pair ij may represent the degree of similarity between the two attributes”, Fig 3, [0041], “The similarity engine 230 may determine similarity scores for attribute pairs ij using the attribute frequency data 145. the similarity score for an attribute pair ij may be determined by taking the inner product of the vectors vi and uj,”, [0054], “For each of the unique attribute pairs, a similarity score for the pair may be determined (307).”, [0055], [0067]); and
generating at least a second value pair for the source item and at least a second competitor item, and for the second value pair: assigning at least a second value to a degree of similarity between the source item and the at least the second competitor item with respect to a feature common to the source item and the at least the second competitor item ([0005], “For each of a plurality of unique attribute pairs, a similarity score may be determined for the pair using the correlation.”, [0030], Fig 3, [0041], [0054], “For each of the unique attribute pairs, a similarity score for the pair may be determined (307).”, [0055], [0067]).
12. Regarding claim 2, Gollapudi teaches the invention as claimed in claim 1 above and further teaches wherein the source item information comprises unstructured text related to the source item ([0023], “This may be because of spelling corrections, the removal of redundant or unimportant terms, or for attribute standardization. For example, the query "Sony TV" may be associated with the attributes "Sony" and "Television", rather than "Sony" and "TV". The attributes may be generated by the search engine 160 or alternatively may be user generated.”).
13. Regarding claim 3, Gollapudi teaches the invention as claimed in claim 1 above and further teaches wherein the at least two tags are further associated with a priority of the at least two attributes within an item group to which the source item belongs (Fig 3, [0030], “the distance engine 140 may use the attribute frequency data 145 to determine the similarities of attribute pairs, as well as a relative importance of an attribute. A determined similarity score of an attribute pair and an importance score of an attribute may then be applied to attributes of a query.”, [0031-0032], “For example, in the query "Sony pink digital camera", the attribute "pink" may have a low importance score (a lowest priority tag) and a high similarity score with the attribute "purple". This may indicate that the attribute "pink" may be removed from the query or substituted with "purple".”, [0045], “the distance engine 140 may substitute one or more attributes of a query with one or more alternate attributes based on the similarity and importance data.”, [0054], “The similarity score may be used to determine the substitutability of an attribute for another attribute. For example, an attribute with a low similarity score with respect to another attribute may not be substitutable with each other, whereas attributes with a high similarity score may essentially be synonyms for one another.”).
14. Regarding claim 4, Gollapudi teaches the invention as claimed in claim 3 above and further teaches wherein the generating of the search term is based at least in part on the priority (Fig 3, [0030], “A determined similarity score of an attribute pair and an importance score of an attribute may then be applied to attributes of a query.”, [0032], “For example, in the query "Sony pink digital camera", the attribute "pink" may have a low importance score and a high similarity score with the attribute "purple". This may indicate that the attribute "pink" may be removed from the query or substituted with "purple".”, [0045], “the distance engine 140 may substitute one or more attributes of a query with one or more alternate attributes based on the similarity and importance data.”, [0054], “The similarity score may be used to determine the substitutability of an attribute for another attribute. For example, an attribute with a low similarity score with respect to another attribute may not be substitutable with each other, whereas attributes with a high similarity score may essentially be synonyms for one another.”).
15. Regarding claim 5, Gollapudi teaches the invention as claimed in claim 1 above and further teaches wherein the generating of each value pair further comprises multiplying the assigned value by a weight value assigned to the first common feature or by a weight value assigned to the feature common to the source item and the at least the second competitor item ([0005], “For each of a plurality of unique attribute pairs, a similarity score may be determined for the pair using the correlation.”, [0030], “The similarity score of an attribute pair ij may represent the degree of similarity between the two attributes”, Fig 3, [0041], “The similarity engine 230 may determine similarity scores for attribute pairs ij using the attribute frequency data 145. the similarity score for an attribute pair ij may be determined by taking the inner product of the vectors vi and uj,”, [0054], “For each of the unique attribute pairs, a similarity score for the pair may be determined (307).”, [0055], [0067]).
16. Regarding claim 6, Gollapudi teaches the invention as claimed in claim 5 above and further teaches wherein computing the similarity score further comprises: for the value pair: assigning a second value to a degree of similarity between the source item and the first competitor item with respect to a second common feature; multiplying the assigned second value by a second weight value assigned to the second common feature; and summing a first result of the multiplication of the assigned value by the weight value and the multiplication of the assigned second value by the second weight value ([0047], see function).
17. Regarding claim 8, Gollapudi teaches the invention as claimed in claim 1 above and further teaches determining which of the first competitor item and the at least the second competitor item is more similar to the source item based on the first value and the at least the second value ([0005], “For each of a plurality of unique attribute pairs, a similarity score may be determined for the pair using the correlation.”, [0030], “The similarity score of an attribute pair ij may represent the degree of similarity between the two attributes”, Fig 3, [0041], “The similarity engine 230 may determine similarity scores for attribute pairs ij using the attribute frequency data 145. the similarity score for an attribute pair ij may be determined by taking the inner product of the vectors vi and uj,”, [0054], “For each of the unique attribute pairs, a similarity score for the pair may be determined (307).”, [0055], [0067]).
Examiner notes and interpretations: When the priority of at least two attributes is defined according to a non-binary schema, it means that the relative importance of those attributes is determined by a system allowing for more than two states (e.g., ordered, weighted, or qualitative levels) rather than a simple true/false or present/absent mechanism.
18. Regarding claim 9, Gollapudi teaches the invention as claimed in claim 3 above and further teaches wherein the priority of the at least two attributes are defined according to a non-binary schema ([0030-0034], [0042-0043], [0053]).
19. Regarding claim 10, Gollapudi teaches the invention as claimed in claim 1 above and further teaches wherein the at least two attributes comprise a first attribute having a first tag and at least a second attribute having at least a second tag, and wherein the method further comprising: extracting the at least the second attribute of the source item from the source item information, the extracting of the at least the second attribute comprising identifying the at least the second tag in the source item information, wherein the at least the second tag is associated with the at least the second attribute of the source item and a priority of the at least the second attribute; wherein the generating of the search term further comprises generating the search term based from the at least one tag and the at least the second tag (claim 1 apply to each attribute of the source item).
20. Regarding claim 11, Gollapudi teaches the invention as claimed in claim 10 above and further teaches wherein the generating of the search term further comprises: generating a first search term comprising the first attribute and the at least the second attribute; and generating a second search term comprising the at least the second attribute, but not the first attribute, based on respective priorities associated with the first tag and the at least the second tag (Fig 3, [0030], “the distance engine 140 may use the attribute frequency data 145 to determine the similarities of attribute pairs, as well as a relative importance of an attribute. A determined similarity score of an attribute pair and an importance score of an attribute may then be applied to attributes of a query.”, [0032], “For example, in the query "Sony pink digital camera", the attribute "pink" may have a low importance score (a lowest priority tag) and a high similarity score with the attribute "purple". This may indicate that the attribute "pink" may be removed from the query or substituted with "purple".”, [0045], “the distance engine 140 may substitute one or more attributes of a query with one or more alternate attributes based on the similarity and importance data.”, [0054], “The similarity score may be used to determine the substitutability of an attribute for another attribute. For example, an attribute with a low similarity score with respect to another attribute may not be substitutable with each other, whereas attributes with a high similarity score may essentially be synonyms for one another.”).
21. Regarding claim 12, Gollapudi teaches the invention as claimed in claim 1 above and further teaches wherein the generating of the first value pair for the source item and the first competitor item further comprises: converting the first value pair into a first vector, the first vector representing similarity between the source item information and the first competitor item information ([0005], “For each of a plurality of unique attribute pairs, a similarity score may be determined for the pair using the correlation.”, [0030], “The similarity score of an attribute pair ij may represent the degree of similarity between the two attributes”, Fig 3, [0041], “The similarity engine 230 may determine similarity scores for attribute pairs ij using the attribute frequency data 145. the similarity score for an attribute pair ij may be determined by taking the inner product of the vectors vi and uj,”, [0054], “For each of the unique attribute pairs, a similarity score for the pair may be determined (307).”, [0055], [0067]).
22. Regarding claim 13, Gollapudi teaches the invention as claimed in claim 12 above and further teaches filtering out at least one value pair that violates a must match constraint ([0003], [0044], best match).
23. Regarding claims 14-18, those claims recite a system performs the method of claims 1-8 respectively and are rejected under the same rationale.
Respond to Amendments and Arguments
24. Applicant has amended claims 1, 3, 5, 8-12, 14, 16, and 18-20 to recite new features and argued that the cited references in combination or isolation do not disclose the claimed invention and nor is the claimed invention obvious in view of the cited references for a number of reasons, including:
Ashkenazi does not disclose "using the search term to search for competitor item information in at least two successive queries, wherein, in each successive query, a lowest priority tag of the at least two tags is sequentially dropped off from the search term," as recited in amended Claim 1, because Ashkenazi does not disclose performing successive queries to retrieve the "list of similar products." (See Ashkenazi at [0031].) Ashkenazi also does not disclose sequentially dropping off the "lowest priority tag" from the "search term" in "each successive query." Instead, Ashkenazi discloses that the "similarity engine ... receives a profile of a product and compares it to the profile of another product. The profile is preferably formed from a collection of some or all the product attributes." (Ashkenazi at [0031].) The similarity searches performed by Ashkenazi' s "similarity engine" do not, however, disclose dropping off attributes from each successive search. Therefore, Ashkenazi does not disclose "using the search term to search for competitor item information in at least two successive queries, wherein, in each successive query, a lowest priority tag of the at least two tags is sequentially dropped off from the search term," as recited in amended Claim 1.
With respect to applicant’s arguments, Applicant’s remarks to the claims have been fully considered but are moot in view of the new ground of rejection necessitated by applicant’s amendment presented above, 35 USC § 102.
CONCLUSION
25. The prior art made of record and not relied upon is considered pertinent to applicant s disclosure.
Bohn et al (US 8280894 B2)
Martinez et al (US 20080140621 A1)
Iyer et al (US 7117163 B1)
Agggarwal et al (US 6728706 B2)
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/HICHAM SKHOUN/Primary Examiner, Art Unit 2164