NDLI: Model-driven restricted-domain adaptation of question answering systems for business intelligence

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Model-driven restricted-domain adaptation of question answering systems for business intelligence

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Model-driven restricted-domain adaptation of question answering systems for business intelligence

Content Provider	ACM Digital Library
Author	Vila, Katia Ferrández, Antonio
Abstract	Business Intelligence (BI) applications no longer limit their analysis to structured databases, but they also need to obtain actionable information from unstructured sources (e.g. data from the Web, etc.). Interestingly, Question Answering (QA) systems are good candidates for these purposes, since they allow users to obtain concise answers to questions stated in natural language from a collection of text documents. Traditionally, QA systems include patterns for dealing with a large spectrum of general questions, namely open-domain question answering (ODQA). However, BI users should be aware of asking questions related to a specific activity of the business (e.g. healthcare, agricultural, transportation, etc.). Therefore, adapting ODQA systems to new restricted domains is an increasingly necessity for these systems to be precisely used in BI. Unfortunately, research addressing this topic has two main drawbacks: (i) patterns are manually tuned, which requires a huge effort in time and cost, and (ii) tuning of patterns is based on analyzing potential questions to be answered, which is not a realistic situation since, in restricted domains, questions are highly complex and difficult to be acquired. To overcome these drawbacks, this paper presents a novel approach based on model-driven development in order to use knowledge resources to automatically and effortlessly adapt patterns of ODQA systems to be useful for restricted-domain BI scenarios.
Starting Page	36
Ending Page	43
Page Count	8
File Format	PDF
ISBN	9781450306102
DOI	10.1145/1966883.1966893
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2011-03-25
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Knowledge organization systems Metamodeling Question answering Model-driven development
Content Type	Text
Resource Type	Article

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