The 30th IPP Symposium
Question Answering: Is More Always Better?
Susan Dumais, Microsoft Research
This talk describes a question-answering system designed to capitalize on the tremendous amount of data now available online. Most question-answering systems use a wide variety of linguistic resources. We focus instead on the redundancy available in large corpora as an important resource. We use this redundancy to simplify the query rewrites that we need to use, and to support answer mining from returned snippets. Experimental results show that question-answering accuracy can be greatly improved by analyzing more and more matching passages. Simple passage ranking and N-gram-extraction techniques work well in our system, making it efficient to use with many backend retrieval engines.
