The Berkeley UNIX Consultant Project
The Berkeley UNIX Consultant Project
Finding similar questions in large question and answer archives
Proceedings of the 14th ACM international conference on Information and knowledge management
Finding experts in community-based question-answering services
Proceedings of the 14th ACM international conference on Information and knowledge management
Gathering knowledge for a question answering system from heterogeneous information sources
HLTKM '01 Proceedings of the workshop on Human Language Technology and Knowledge Management - Volume 2001
A framework to predict the quality of answers with non-textual features
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
An intelligent fuzzy-based recommendation system for consumer electronic products
Expert Systems with Applications: An International Journal
Corpus-based Pattern Induction for a Knowledge-based Question Answering Approach
ICSC '07 Proceedings of the International Conference on Semantic Computing
Discovering authorities in question answer communities by using link analysis
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Finding high-quality content in social media
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Finding the right facts in the crowd: factoid question answering over social media
Proceedings of the 17th international conference on World Wide Web
Exploring the Application of Fuzzy Logic and Data Fusion Mechanisms in QAS
WILF '07 Proceedings of the 7th international workshop on Fuzzy Logic and Applications: Applications of Fuzzy Sets Theory
Dealing with Spoken Requests in a Multimodal Question Answering System
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
Baseball: an automatic question-answerer
IRE-AIEE-ACM '61 (Western) Papers presented at the May 9-11, 1961, western joint IRE-AIEE-ACM computer conference
Quality-aware collaborative question answering: methods and evaluation
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Progress in natural language understanding: an application to lunar geology
AFIPS '73 Proceedings of the June 4-8, 1973, national computer conference and exposition
A syntactic tree matching approach to finding similar questions in community-based qa services
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Expert identification in community question answering: exploring question selection bias
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Improved answer ranking in social question-answering portals
Proceedings of the 3rd international workshop on Search and mining user-generated contents
QUASAR: the question answering system of the universidad politécnica de valencia
CLEF'05 Proceedings of the 6th international conference on Cross-Language Evalution Forum: accessing Multilingual Information Repositories
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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.