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 ...

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.