Overview of the INEX 2010 question answering track (QA@INEX)
|Overview of the INEX 2010 question answering track (QA@INEX)|
|Author(s)||SanJuan E., Bellot P., Moriceau V., Tannier X.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Unknown (Extra: Complex questions, Document Retrieval, KL-divergence, Kullback-Leibler divergence, Question Answering, Question Answering track, Summarization systems, Wikipedia, Lakes, XML, Natural language processing systems)|
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Overview of the INEX 2010 question answering track (QA@INEX) is a 2011 conference paper written in English by SanJuan E., Bellot P., Moriceau V., Tannier X. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
The INEX Question Answering track (QA@INEX) aims to evaluate a complex question-answering task using the Wikipedia. The set of questions is composed of factoid, precise questions that expect short answers, as well as more complex questions that can be answered by several sentences or by an aggregation of texts from different documents. Long answers have been evaluated based on Kullback Leibler (KL) divergence between n-gram distributions. This allowed summarization systems to participate. Most of them generated a readable extract of sentences from top ranked documents by a state-of-the-art document retrieval engine. Participants also tested several methods of question disambiguation. Evaluation has been carried out on a pool of real questions from OverBlog and Yahoo! Answers. Results tend to show that the baseline-restricted focused IR system minimizes KL divergence but misses readability meanwhile summarization systems tend to use longer and stand-alone sentences thus improving readability but increasing KL divergence.
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