DETERMINING PRODUCT CATEGORIES BY MINING INTERACTION DATA IN CHAT TRANSCRIPTS

• US 20140195562A1
• Filed: 12/31/2013
• Published: 07/10/2014
• Est. Priority Date: 01/04/2013
• Status: Active Grant

• Current Assignee: [24]7.ai, Inc.
• Original Assignee: 24/7 Customer Incorporated
• Inventors: HARDENIYA, Nitin Kumar, SRI, R. Mathangi, VIJAYARAGHAVAN, Ravi
• Granted Patent: US 9,460,455 B2
• Time in Patent Office: Days
• US Class Current: 707/776
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06Q 30/01 Customer relationship services
• CPC Class Codes: G06Q 30/0256 User search

Abstract

The propensity and intent of a user to make a purchase is predicted based on product search queries and chat streams. The contents of the data sources, including search queries and chat streams, are analyzed for product names and product attributes. The results of the analyses are used to predict user needs. Product names and attributes are extracted from the data sources. The extracted information is mapped onto abstract product categories. Based on the abstract product categories, offers for products and services are made to the user.

Claims

1. A computer implemented method for user analysis, comprising:

providing a processor configured for obtaining a query from a user during a chat communication;

said processor configured for extracting keywords from the user query that describe products and product attributes;

said processor configured for mapping said keywords to abstract product categories;

said processor configured for inferring the user'"'"'s based on the abstract product categories; and

said processor configured for recommending offers for the user based on the abstract product categories and the user'"'"'s intent.

2. The method of claim 1, wherein keywords are extracted from one or more user communication channels that comprise any of search queries and chat streams.

3. The method of claim 1, further comprising:

determining product categories by text mining interaction data in one or more chat transcripts.

4. The method of claim 1, further comprising:

a client device communicating with an agent module via a network;

wherein during said communication with said agent module a user, via said client device, describes or discloses any of certain product related features, product names, and any other product relevant information;

wherein said information is contained in a transcript of a chat session between said user and an agent.

5. The method of claim 1, further comprising providing a Web server that comprises:

a collection module configured for collecting a historical data set recorded by, and received by, one or more search engines;

a category determination module configured for managing determination of appropriate categories and query aspects for each of a plurality of categories and for identifying one or more appropriate categories to associate with a query;

a collection module configured for collecting keywords, specified categories, and selection of various aspects tracked by a search engine;

a data processing module configured for processing said collected historical data set from said collection module; and

a database configured for storing determined appropriate categories and top number of key words and tags associated with a search query.

6. The method of claim 3, further comprising:

initially extracting a primary line from said chat transcript, said primary line comprising data regarding an interaction between a client device and an agent module;

passing said extracted primary line through a dependency parser which, in turn, outputs a parsed tree; and

based on said parsed tree, implementing a heuristic based approach to extract a product name or other such relevant information from said chat transcript.

7. The method of claim 3, further comprising:

using a sentence splitter for pre-processing.

8. The method of claim 3, further comprising:

post processing using any of stop-word removal, spelling correction, and domain specific word removal to obtain cleaner product related information.

9. The method claim 1, said mapping further comprising:

performing product-to-category mapping in which, once a product name and other product relevant information is extracted from a chat session, said information is mapped to an abstract product category to provide insights that are used to produce an actionable recommendation.

10. The method of claim 9, further comprising:

mapping specific domains that comprise entities through an ontology that provides different ontological relations that are used to map a product name, part, and information to product categories.

11. The method of claim 9, further comprising:

mapping a product name to a product category using a family of semantic distance measures with which a semantic similarity measure derived from a number of hits returned by a search engine for a given set of keywords;

wherein keywords having a same or similar meaning in a natural language sense are close in units of distance; and

wherein words with dissimilar meanings are farther apart;

using said semantic distance measures to calculate semantic relatedness, wherein said relatedness contributes to a mapping between a product name and a product category.

12. The method of claim 11, further comprising:

using a vocabulary as a metric to calculate semantic relatedness from where it is possible to map a product name to a product category.

13. The method of claim 3, further comprising:

text mining any of promotions, offers, add-on offers, and related parts for a same chat conversation and any other interaction data between a client device and an agent module to create at least one correlation between these attributes and further leads for recommending actions to operations and for agent training.

14. The method of claim 3, further comprising:

a chat client providing access to a knowledge base for agents, wherein said knowledge base recommends offers for a specific product category and related parts for said specific product category.

15. The method of claim 14, wherein said knowledge base provides competitor analysis and offers and deals for specific product categories

16. The method of claim 14, further comprising:

using social media data, considering pros and cons for a specific product category, along with the sentiment and subjectivity analysis for any of a specific product category, brand, and name.

17. The method of claim 1, further comprising:

making all of said recommendations at an aggregate level and performing said recommendations offline over time.

18. The method of claim 1, further comprising:

personalizing said recommendations to a specific user visit, wherein each element of real time mining through Web, chat, and social channels generates more personalized recommendations.

19. The method of claim 1, further comprising:

determining product categories in real time.

20. The method of claim 1, further comprising:

said processor configured using the abstract product categories and the user'"'"'s intent for any of offline analysis, context passing to other channels of interaction, analyzing agent performance, and enhancing the user'"'"'s experience.

21. An apparatus for user analysis, comprising:

a processor obtaining a query from a user during a chat communication;

said processor extracting keywords from the user query that describe products and product attributes;

said processor mapping said keywords to abstract product categories;

said processor inferring the user'"'"'s based on the abstract product categories; and

said processor recommending offers for the user based on the abstract product categories and the user'"'"'s intent.