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Using Graded-Relevance Metrics for Evaluating Community QA Answer Selection

Using Graded-Relevance Metrics for Evaluating Community QA Answer Selection

This video was recorded at Fourth ACM International Conference on Web Search and Data Mining - WSDM 2011. Community Question Answering (CQA) sites such as Yahoo! Answers have emerged as rich knowledge resources for information seekers. However, answers posted to CQA sites can be irrelevant, incomplete, redundant, incorrect, biased, ill-formed or even abusive. Hence, automatic selection of "good" answers for a given posted question is a practical research problem that will help us manage the quality of accumulated knowledge. One way to evaluate answer selection systems for CQA would be to use the Best Answers (BAs) that are readily available from the CQA sites. However, BAs may be biased, and even if they are not, there may be other good answers besides BAs. To remedy these two problems, we... Show More

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