22 |
Insights from the Women in Combat Symposium
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In: DTIC (2013)
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23 |
Automated Extraction and Characterisation of Social Network Data from Unstructured Sources -- An Ontology-Based Approach
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In: DTIC (2013)
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24 |
Interacting with Multi-Robot Systems Using BML
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In: DTIC (2013)
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25 |
Making Semantic Information Work Effectively for Degraded Environments
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In: DTIC (2013)
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26 |
Accelerating Exploitation of Low-grade Intelligence through Semantic Text Processing of Social Media
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In: DTIC (2013)
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28 |
QUT Para at TREC 2012 Web Track: Word Associations for Retrieving Web Documents
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In: DTIC (2012)
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30 |
Phoneme Class Based Adaptation for Mismatch Acoustic Modeling of Distant Noisy Speech (Preprint)
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In: DTIC (2012)
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31 |
Conference Report: Cultural and Linguistic Advancement for Mission Success: Enhancing Language, Regional and Cultural Capabilities Across Whole of Government for an Effective COIN Strategy
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In: DTIC (2012)
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33 |
Machine Recognition vs Human Recognition of Voices
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In: DTIC (2012)
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34 |
Speaker Clustering for a Mixture of Singing and Reading (Preprint)
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In: DTIC (2012)
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35 |
Applications of Lexical Link Analysis Web Service for Large-Scale Automation, Validation, Discovery, Visualization, and Real-Time Program-Awareness
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In: DTIC (2012)
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36 |
Compressed Domain Automatic Level Control Based on ITU-T G.722.2
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In: DTIC (2012)
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37 |
Integrating Hard and Soft Information Sources for D2D Using Controlled Natural Language
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In: DTIC (2012)
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38 |
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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39 |
Aligning Learning Capability with Strategy: A Training Needs Assessment (TNA) Case Study
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In: DTIC (2012)
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40 |
Learning for Microblogs with Distant Supervision: Political Forecasting with Twitter
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In: DTIC (2012)
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