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A Hybrid Approach to Clinical Question Answering
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In: DTIC (2014)
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| 2 |
Towards a Simple and Efficient Web Search Framework
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In: DTIC (2014)
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| 4 |
Distributed Non-Parametric Representations for Vital Filtering: UW at TREC KBA 2014
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In: DTIC (2014)
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| 5 |
Modelling Psychological Needs for User-dependent Contextual Suggestion
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In: DTIC (2014)
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| 6 |
Making Semantic Information Work Effectively for Degraded Environments
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In: DTIC (2013)
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| 7 |
Accelerating Exploitation of Low-grade Intelligence through Semantic Text Processing of Social Media
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In: DTIC (2013)
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| 8 |
QUT Para at TREC 2012 Web Track: Word Associations for Retrieving Web Documents
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In: DTIC (2012)
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| 9 |
Adding a Capability to Extract Sentiment from Text Using HanDles
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In: DTIC (2012)
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| 10 |
Speaker Clustering for a Mixture of Singing and Reading (Preprint)
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In: DTIC (2012)
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| 11 |
Horizontal Integration of Warfighter Intelligence Data: A Shared Semantic Resource for the Intelligence Community
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In: DTIC (2012)
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| 12 |
SAWUS: Siena's Automatic Wikipedia Update System
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In: DTIC (2012)
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Abstract:
The National Institute of Standards and Technology (NIST) has been running an annual Text Retrieval Competition and Conference (TREC) since 1992. This is a premier conference that offers researchers in the field of Computational Linguistics the opportunity to showcase their work and compare their results against other leading researchers. Our Siena research team participated in the TREC Knowledge Based Acquisition (KBA) Track which was offered for the first time in 2012. The objective of this track is to drive research into automatic acquisition of knowledge such as automatically updating Wikipedia by utilizing online news. Specifically our team of researchers developed a system that filters a stream of content for information that should be included on a given Wikipedia page. It was not yet clear how traditional Information Retrieval (IR) techniques perform for this task therefore we began with a baseline test using current state of the art IR techniques. We then went on to experiment with query expansion building a module that utilized Wikipedia Infoboxes to add terms to our query. This module was incorporated with our IR component to create SAWUS. Four submissions were sent to NIST to undergo a formal evaluation. ; Presented at the Twenty-First Text REtrieval Conference (TREC 2012) held in Gaithersburg, Maryland, November 6-9, 2012. 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). U.S. Government or Federal Rights License
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Keyword:
*INFORMATION RETRIEVAL; AUTOMATIC; DATA ACQUISITION; Information Science; INTERNET; QUERY EXPANSION; SYMPOSIA; WIKIPEDIA
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URL: http://www.dtic.mil/docs/citations/ADA581303
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA581303
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| 13 |
CSSG: Learning within NLP Pipelines for Scalable Data Mining and Information Extraction
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In: DTIC (2011)
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| 14 |
Entity List Completion Using Set Expansion Techniques
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In: DTIC (2011)
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| 15 |
Related Entity Finding: University of Waterloo at TREC 2010 Entity Track
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In: DTIC (2010)
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| 16 |
Enhancing a Web Crawler with Arabic Search Capability
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In: DTIC (2010)
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| 17 |
Extrinsic Evaluation of Automated Information Extraction Programs
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In: DTIC (2010)
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| 19 |
A Novel Framework for Related Entities Finding: ICTNET at TREC 2009 Entity Track
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In: DTIC (2009)
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| 20 |
Relevance Feedback based on Constrained Clustering: FDU at TREC 09
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In: DTIC (2009)
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