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Opinosis: A Graph Based Approach to Abstractive Summarization of Highly Redundant Opinions
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Finding Related Entities by Retrieving Relations: UIUC at TREC 2009 Entity Track
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In: DTIC (2009)
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Abstract:
Our goal in participating in the TREC 2009 Entity Track was to study whether relation extraction techniques can help in improving accuracy of the entity finding task. Finding related entities is informational in nature and we wanted to explore if inducing structure on the queries helps satisfy this information need. The research outlook we took was to study techniques that retrieve relations between two entities from a large corpus, and from those, find the most relevant entities that participate in the given relation with another given entity. Instead of aiming at retrieving pages about specific entities, we tried to address the problem of directly finding the entities from the text. Our experimental results show that we were able to find many related entities using relation-based extraction, and ranking entities based on further evidence from the text helps to a certain extent. ; Presented at the Text REtrieval Conference (TREC 2009) (18th) held in Gaithersburg, Maryland, November 17-20, 2009. Published in Proceedings of the Text REtrieval Conference (TREC 2009) (18th), 2009. The conference was co-sponsored by the National Institute of Standards and Technology (NIST) the Defense Advanced Research Projects Agency (DARPA) and the Advanced Research and Development Activity (ARDA). The original document contains color images.
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Keyword:
*INFORMATION RETRIEVAL; ACCURACY; ENTITIES; EXTRACTION; FORMULATIONS; Information Science; SYMPOSIA; SYSTEMS ENGINEERING
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA517759
http://www.dtic.mil/docs/citations/ADA517759
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Automated Story Capture From Conversational Speech
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In: DTIC (2005)
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