Hierarchic model and natural language analyzer

• US 10,067,965 B2
• Filed: 09/26/2016
• Issued: 09/04/2018
• Est. Priority Date: 09/26/2016
• Status: Active Grant

• Current Assignee: Scotilev Limited
• Original Assignee: Twiggle, Ltd.
• Inventors: Lev, Iddo, Shalom, Eli, Avidor, Adi
• Primary Examiner(s): Chbouki, Tarek
• Application Number:
  US15/275,620
• Publication Number:
  US 20180089242A1
• Time in Patent Office: 708 Days
• CPC Class Codes: G06F 16/212 with details for data modelling support
• CPC Class Codes: G06F 16/2228 Indexing structures
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 40/30 Semantic analysis

Abstract

A system and method for interpretation of product-related data, including extracting product information from a product-related dataset of an e-commerce data source, determining at least one representation of the product information by elements of a product database model, by finding model elements corresponding to elements of the product information and selecting model elements that form consistent representation of the product information with hierarchic relations between the model elements, and creating an indexed product database by indexing according to the representing model elements the at least one determined representation of the product information.

Claims

1. A system for creating a response to a search query using product-related data, comprising:

at least one memory which stores an indexed hierarchic product database and a hierarchic product model arranging a plurality of product categories in a hierarchy, said hierarchic product model defines a plurality of attributes for each one of said plurality of product categories and a plurality of values for each of said plurality of attributes; and

at least one hardware processor executing a code for;

receiving natural language product information for each of a plurality of products from a product-related dataset of an e-commerce data source, said natural language product information defining product information elements descriptive of a respective said product;

for each of said plurality of products automatically indexing one of a plurality of modeled product representations into said indexed hierarchic product database according to said hierarchic product model, said indexing into said indexed hierarchic product database is performed by;

creating a respective modeled product representation for said each product, said respective modeled product representation comprising at least some of a plurality of model elements, said plurality of model elements comprising said plurality of product categories, said plurality of attributes and said plurality of values of said hierarchic product model, said selected model elements are corresponding to at least one of synonyms and similar terms of said product information elements extracted, according to a natural language analysis (NLA), from a respective said natural language product information of said respective product,

extracting, from said hierarchic product model, a plurality of hierarchic relations between said selected model elements, and

indexing said respective modeled product representation of said respective product in said indexed hierarchic product database according to said selected model elements and said plurality of hierarchic relations;

receiving a natural language search query comprising at least one searched product information element indicative of at least one searched product;

modeling said natural language search query to create a modeled search query comprising at least one of said plurality of model elements corresponding to said at least one searched product information element extracted from said natural language search query;

automatically matching said modeled search query with at least some of said plurality of modeled product representations defined in said indexed hierarchic product database and retrieving matching said modeled product representations; and

transmitting a response to said natural language search query, said response comprising said matching modeled product representations.

2. The system of claim 1, wherein the processor is configured to execute code for detecting among the selected model elements a model element of high hierarchy relative to the other selected model elements, and filtering out possible representing model elements which are inconsistent with the high hierarchy model element.

3. The system of claim 1, wherein each of the selected model elements represents at least one of:

a list comprising a product-related concept, an attribute of a concept, an enriched attribute depending on other attributes, a value of an attribute or a limitation on an attribute'"'"'s value space;

wherein a concept is a model element representing a certain kind of products or parts of products and an attribute is a model attribute representing properties of the concept.

4. The system of claim 3, wherein the processor is configured to execute code for receiving along with natural language product information an indication about a product, a concept, an attribute and/or a value thereof, to which the natural language product information relate, and limiting the plurality of selected model elements to the indicated product, concept, attribute and/or value.

5. The system of claim 3, wherein each of the selected model elements includes an instance of a concept representing a concept with a specific value of at least one of its attributes.

6. The system of claim 5, further comprising at least one of the plurality of model elements has at least one secondary attribute used for creating at least one of said plurality of modeled product representations and/or for modeling the modeled search query.

7. The system of claim 1, wherein the hierarchic relations include at least one of inheritance and partonomy.

8. The system of claim 1, wherein each of the plurality of selected model elements corresponding to a term includes the same term, a similar term and/or a synonym of the term.

9. The system of claim 1, wherein the processor is configured to execute code for the modeling an input text by determining at least one representation of the natural language search query received from a search server by elements of the hierarchic product model which are corresponding to elements of the natural language search query;

wherein said plurality of selected model elements form a consistent representation of the natural language search query with hierarchic relations between the plurality of model elements;

wherein the processor is configured to execute code for the automatically creating a response by transmitting the determined at least one representation to the search server, thus enabling the search server to match the at least one representation of the natural language search query to modeled representations of products stored in the indexed hierarchic product database.

10. The system of claim 9, wherein the processor is configured to execute code for filtering possible representing model elements in a pre-defined manner when corresponding pre-defined expressions are included in the natural language search query, a pre-defined expression is indicative of at least one of a list comprising a relation, a threshold, and a value restriction.

11. The system of claim 10, wherein the pre-defined expressions include at least one of a list comprising the expressions:

less than, more than, between, cheap, large, small and best for.

12. The system of claim 10, wherein the processor is configured to execute code for filtering out all products with a price above a predetermined threshold value when a corresponding expression is included in the natural language search query.

13. The system of claim 12, wherein the threshold value depends on a concept identified in the natural language search query.

14. The system of claim 10, wherein the processor is configured to execute code for calculating, in response to an expression included in the natural language search query, a certain value of an enriched attribute based on one or more attributes, and filtering out products that don'"'"'t fit the value.

15. The system of claim 1, wherein the processor is configured to execute code for identifying an attribute to which a value in the natural language product information refers to, according to a space of possible values of the the model attribute implemented in the hierarchic product model.

16. The system of claim 1, wherein the processor is configured to execute code for ranking a possible representing model element of the plurality of model elements according to frequency of use deduced from value distributions implemented in the hierarchic product model.

17. The system of claim 1, wherein the processor is configured to execute code for identifying a model attribute to which a value in the natural language product information refers, according to data implemented in the hierarchic product model ascribing customary attributes to corresponding concepts.

18. The system of claim 1, wherein the processor is configured to execute code for identifying which of several possible model elements of the plurality of model elements the natural language product information refers to, according to attributes each of the possible model elements can have.

19. The system of claim 1, wherein the processor is configured to execute code for interpreting separate terms of the natural language product information as a concept, a category, an attribute, and/or a value of the attribute, respectively.

20. The system of claim 1, wherein the processor is configured to execute code for calculating a Boolean value of a model attribute and filter out possible representations based on the calculated Boolean value.

21. A method for creating a response to a natural language search query using product-related data, comprising:

providing an indexed hierarchic product database and a hierarchic product model arranging a plurality of product categories in a hierarchy, said hierarchic product model defines a plurality of attributes for each one of said plurality of product categories and a plurality of values for each of said plurality of attributes;

receiving natural language product information for each of a plurality of products from a product-related dataset of an e-commerce data source, said natural language product information defining product information elements descriptive of a respective said product;

for each of said plurality of products automatically indexing one of a plurality of modeled product representations into said indexed hierarchic product database according to said hierarchic product model, said indexing into said indexed hierarchic product database is performed by;

creating a respective modeled product representation for said each product, said respective modeled product representation comprising at least some of a plurality of model elements, said plurality of model elements comprising said said plurality of product categories, said plurality of attributes and said plurality of values of said hierarchic product model, said selected model elements are corresponding to at least one of synonyms and similar terms of product information elements extracted, according to a natural language analysis (NLA), from a respective said natural language product information of said respective product,

extracting from said hierarchic product, a plurality of hierarchic relations between said selected model attributes, and

indexing said respective modeled product representation of said respective product in said indexed hierarchic product database according to said selected model elements and said plurality of hierarchic relations;

receiving a natural language search query comprising at least one searched product information element indicative of at least one searched product;

modeling said natural language search query to create a modeled search query comprising at least one of said plurality of model elements corresponding to said at least one searched product information element extracted from said natural language search query; and

automatically matching said modeled search query with at least some of said plurality of modeled product representations defined in said indexed hierarchic product database and retrieving matching said modeled product representations; and

transmitting a response to said natural language search query, said response comprising said matching modeled product representations.

22. The method of claim 21, wherein said modeling comprises:

determining at least one representation of the natural language search query received from a search server by elements of the hierarchic product model, by finding at least some of the plurality of model elements corresponding to the at least one searched product information elements in the hierarchic product model and selecting model elements that form consistent representation of the natural language search query with hierarchic relations between the selected model elements;

wherein said automatically creating comprises transmitting the at least one representation to the search server, thus enabling the search server to match the at least one representation of the natural language search query to modeled representations of products stored in the indexed hierarchic product database.