BioinQA: metadata-based multi-document QA system for addressing the issues in biomedical domain. (1st January 2013)

• Record Type: Journal Article
• Authors: Mittal, Sparsh; Gupta, Saket; Mittal, Ankush
• Is Part Of: International journal of data mining, modelling and management. Volume 5:Number 1(2013)
• Page Start: 37
• Page End: 56
• Publication Date: 2013-01-01
• Subjects: question answering system -- QAS -- biomedical -- metadata -- multi-document QAS -- evaluation metric MCRR -- data mining -- comparison -- heterogeneity; Data mining -- Periodicals; Information science -- Periodicals; Databases -- Periodicals; 005.7
• Languages: English
• ISSNs: 1759-1163

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.