Abstract
Owing to the vast amount of information readily available on the World Wide Web, there has been a significant increase in the number of online question answering QA systems. A branch of QA systems that has seen such remarkable growth is the community-based question answering CQA systems. In this paper, the authors propose a method that is proactive enough to provide answers to questions and additionally offers word definitions, with the aim of reducing the time lag that results from askers having to wait for answers to a question from various users. Additionally, it designs a method to evaluate and predict the quality of an answer in a CQA setting, based on experts' rating. It uses fuzzy logic to aggregate the ratings and provide ranked answers in return. Experimental results with computing-related datasets from Yahoo! Answers demonstrate the effectiveness of the proposed techniques.
Sign-in/Register to access full text options 
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 callDisclaimer: 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.
