C4.5: programs for machine learning
C4.5: programs for machine learning
Scaling question answering to the Web
Proceedings of the 10th international conference on World Wide Web
Mining the web for answers to natural language questions
Proceedings of the tenth international conference on Information and knowledge management
Fusion of AV features and external information sources for event detection in team sports video
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Mining web snippets to answer list questions
AIDM '07 Proceedings of the 2nd international workshop on Integrating artificial intelligence and data mining - Volume 84
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The wealth of information available on the web makes it an attractive resource for seeking quick answers. While web-based question answering becomes an emerging topic in recent years, the problem of efficiently locating a complete set of distinct answers on the Web is far from being solved. We introduce our system, FADA, which relies on question event analysis, web page clustering, and natural language parsing, to find reliable distinct answers with high recall. The method has been found to be effective in strengthening state-of-the-art Web question answering techniques by emphasizing on answer completeness and uniqueness.