Invention Grant
- Patent Title: System and method for generating full questions from natural language queries
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Application No.: US15261339Application Date: 2016-09-09
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Publication No.: US10339168B2Publication Date: 2019-07-02
- Inventor: Bryn R. Dole , William S. Ko , Malous M. Kossarian , Douglas A. Smith
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Pepper Hamilton LLP
- Main IPC: G06F16/00
- IPC: G06F16/00 ; G06F16/33 ; G06F17/28 ; G06N5/04 ; G06F17/27 ; G06F16/332

Abstract:
Embodiments provide a computer implemented method, in a data processing system comprising a processor and a memory comprising instructions which are executed by the processor to cause the processor to implement a full question generation system, the method comprising ingesting, into the full question generation system, a query dataset derived from one or more search queries entered by one or more users of an internet search engine; identifying questions from the ingested query dataset; separating, through a full question identification module, one or more prior full questions from the ingested dataset; identifying, through a question intent query identification module, one or more question intent queries from the query dataset; for each identified question intent query: sorting, through a sorting module, the question intent query into one or more bins based on one or more missing interrogative words; and appending, through an appending module, the missing interrogative word and a verb onto the question intent query to generate a full question; and ingesting, through the cognitive system, the one or more generated full questions as training dataset. The full question generation method can additionally generate un-canonical questions.
Public/Granted literature
- US20180075366A1 SYSTEM AND METHOD FOR GENERATING FULL QUESTIONS FROM NATURAL LANGUAGE QUERIES Public/Granted day:2018-03-15
Information query