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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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Abstract:
DoD acquisition is an extremely complex system, comprised of myriad stakeholders, processes, people, activities, and organizational structures. Processes within this complex system are encumbered by the continuous development of large amounts of unstructured and unformatted acquisition program data, which is narrowly useful, but difficult to aggregate across the enterprise. Yet, acquisition analysts and decision-makers must analyze all types and spectrums of the available data to obtain a complete and understandable picture. This is a kind of systems non-congruence that has been difficult to overcome. For those embedded within the complexities of the acquisition community, this can be a daunting, if not impossible, task. We will apply a data-driven automation system, namely, Lexical Link Analysis (LLA) to facilitate acquisition researchers and decision-makers to recognize important connections (concepts) that form patterns derived from dynamic, ongoing data collection. The LLA technology and methodology is used to uncover and display relationships among competing programs and Navy-driven requirements. In the past year, we tested our method using samples of acquisition data for visualization and validity. LLA successfully discovered statistically significant correlations, and automatically extracted lexical links, thus improving acquisition professionals knowledge. ; Excerpt from the Proceedings of the Annual Acquisition Research Symposium (9th) held in Monterey, CA on 15-17 May 2012, Volume 1.
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Keyword:
*DATA ACQUISITION; DISPLAY SYSTEMS; EXTRACTION; Information Science; INTELLIGIBILITY; LEXICOGRAPHY; LLC(LEXICAL LINK ANALYSIS); PICTURES; SYMPOSIA
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA563319 http://www.dtic.mil/docs/citations/ADA563319
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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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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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