BioinQA: metadata-based multi-document QA system for addressing the issues in biomedical domain

Sparsh Mittal, Saket Gupta and Ankush Mittal

International Journal of Data Mining, Modelling and Management, 2013, vol. 5, issue 1, 37-56

Abstract: Despite the availability of large amount of biomedical literature, extracting relevant information catering to the exact need of the user has been difficult in the absence of efficient domain specific information retrieval tools. Biomedical question answering (QA) systems require special techniques to address domain-specific issues, since a wide variety of user-groups having different information needs - terminology and level of understanding, etc. - may access the information. While specialised information retrieval tools are not suitable for beginners, general purpose search engines are not intelligent enough to respond to domain specific questions. This paper presents an intelligent QA system that answers natural language questions while adapting itself to the level of user. The system constructs answers from multiple documents for complex comparison seeking questions. The system utilises metadata knowledge for addressing specific biomedical domain concerns like heterogeneity, acronyms, etc. Experiments performed show superiority of the system over popular commercial search engines such as Google, etc.

Keywords: question answering systems; intelligent QAS; biomedical QAS; metadata; multi-document QAS; evaluation metric MCRR; data mining; comparison; heterogeneity; information retrieval; natural language queries; domain specific questions; search engines. (search for similar items in EconPapers)
Date: 2013
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