Method For Recommending Content To Ingest As Corpora Based On Interaction History In Natural Language Question And Answering Systems

• US 20160196491A1
• Filed: 09/22/2015
• Published: 07/07/2016
• Est. Priority Date: 01/02/2015
• Status: Active Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Chandrasekaran, Swaminathan, Dandala, Bharath, Krishnamurthy, Lakshminarayanan, Richardson, Alvin C.
• Application Number:
  US14/861,498
• Publication Number:
  US 20160196491A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/26 Visual data mining; Browsing structured data
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

An approach is provided for generating actionable content ingestion recommendations based on an interaction history that is mined to extract interaction context parameters from questions and answer results that meet specified answer deficiency criteria by searching one or more content sources using the extracted interaction context parameters to identify new content that is relevant to improving the first answer, and then presenting the new content in an actionable content ingestion recommendation list for display and review by a domain expert, where the actionable content ingestion recommendation list recommends the new content for ingestion in a knowledge base corpus.

Claims

1. A method of generating actionable content ingestion recommendations, the method comprising:

mining, by an information handling system comprising a processor and a memory, an interaction history comprising a plurality of questions and answer results for a plurality of users to extract interaction context parameters for at least a first answer that meets specified answer deficiency criteria;

searching, by the information handling system, one or more content sources using the extracted interaction context parameters along with multi-factorial variable or attributes about the users to identify new content that is relevant to improving the first answer or adding new answers to a candidate answer list; and

presenting, by the information handling system, an actionable content ingestion recommendation for display and review by a domain expert, where the actionable content ingestion recommendation lists the new content for ingestion in a knowledge base corpus.

2. The method of claim 1, further comprising storing, by an information handling system capable of answering questions, the plurality of questions and answer results in the interaction history.

3. The method of claim 1, where mining the interaction history comprises performing, by the information handling system, a natural language processing (NLP) analysis of each question and answer in the interaction history to at least extract key terms, question sentiment, question focus, N-grams, and lexical answer type information, from a first question corresponding to the first answer.

4. The method of claim 1, where mining the interaction history comprises performing, by the information handling system, a natural language processing (NLP) analysis of each question and answer in the interaction history, wherein the NLP analysis extracts one or more profile parameters for each user that submitted a question stored in the interaction history.

5. The method of claim 4, where the one or more profile parameters for each user comprise a first user location and time information for when a question was submitted by said user.

6. The method of claim 1, where mining the interaction history comprises performing, by the information handling system, an association analysis of each question and answer in the interaction history to identify one or more questions and associated comments that are similar to a first question corresponding to the first answer.

7. The method of claim 6, where performing an association analysis comprises applying, by the information handling system, a collaborative filtering or market-based analysis to make automatic associations between questions from different users when identifying the one or more questions and associated comments.

8. The method of claim 1, where mining the interaction history comprises filtering, by the information handling system, the extracted interaction context parameters using a multifactorial topical model, such as a Latent Dirichlet Allocation (LDA) or Latent Semantic Analysis (LSA) model.

9. The method of claim 1, where searching one or more content sources comprises using the extracted interaction context parameters to search against a document repository, enterprise content management (ECM) system, knowledge management system (KMS), or cloud-based document repository.

10. The method of claim 1, where the first answer meets the specified answer deficiency criteria if the first answer has a confidence measure below a minimum confidence threshold, if the first answer provides no response, if the first answer has an associated negative sentiment, if there are repeated questions relating to the first answer, or if the first answer has no supporting evidence.

11. The method of claim 1, further comprising selecting, by the domain expert, the new content for ingestion in the knowledge base corpus.

12-21. -21. (canceled)