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Neural Methods Towards Concept Discovery from Text via Knowledge Transfer
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In: http://rave.ohiolink.edu/etdc/view?acc_num=osu1572387318988274 (2019)
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| 2 |
The Impact of Name-Matching and Blocking on Author Disambiguation
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In: Proceedings of the 27th ACM Conference on Information and Knowledge Management ; 803-812 ; ACM International Conference on Information and Knowledge Management (CIKM) "From Big Data and Big Information to Big Knowledge" ; 27 (2018)
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Principles of content analysis for information retrieval systems: an overview
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In: Text analysis and computers ; 1 ; ZUMA-Nachrichten Spezial ; 76-99 ; Text Analysis and Computers Conference (2017)
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A Hybrid Approach to Clinical Question Answering
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In: DTIC (2014)
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| 5 |
Towards a Simple and Efficient Web Search Framework
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In: DTIC (2014)
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| 7 |
Distributed Non-Parametric Representations for Vital Filtering: UW at TREC KBA 2014
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In: DTIC (2014)
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| 8 |
Modelling Psychological Needs for User-dependent Contextual Suggestion
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In: DTIC (2014)
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| 9 |
Using a Bayesian Model to Combine LDA Features with Crowdsourced Responses
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In: DTIC (2013)
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| 10 |
Lexical Link Analysis Application: Improving Web Service to Acquisition Visibility Portal
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In: DTIC (2013)
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| 11 |
Making Semantic Information Work Effectively for Degraded Environments
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In: DTIC (2013)
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Abstract:
The challenges of effectively managing semantic technologies over disadvantaged or degraded environments are numerous and complex. One of the greatest challenges is the size of raw data. Large messages prevent semantics from being operationally effective by overflowing the available bandwidth and memory resources of degraded environments. Our approach mitigates this challenge by performing data reduction through the adoption of format recognition technologies, semantic data extractions, and the application of mission-based and role-based filters. The other challenge is that semantics are not especially effective in degraded environments due to a lack of interoperability with standardized DoD messaging formats and resource limitations for processing, storage, reasoning, and bandwidth. Our approach increases the utility of semantics by extracting attributes that correlate with DoD messaging standards and collaborate with mission-based domain ontologies, as well as to relocate the intensive processing, storage, bandwidth, and semantic extraction applications to enterprise services. This enables semantics to be utilized effectively, regardless of environment, while simultaneously informing quality of service and role-based policy decisions. ; Presented at the 18th International Command and Control Research and Technology Symposium (ICCRTS) C2 in Underdeveloped, Degraded and Denied Operational Environments held in Alexandria, VA, on 19-21 June 2013.
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Keyword:
*DATA REDUCTION; *DEGRADED ENVIRONMENTS; *EXTRACTION; *INFORMATION RETRIEVAL; *INTEROPERABILITY; *MIDDLEWARE; *SEMANTIC TECHNOLOGIES; *SEMANTICS; *STANDARDS; BANDWIDTH; COMPUTATIONAL LINGUISTICS; Computer Programming and Software; D2I(DATA TO INFORMATION); DATA REFERENCING; DATA REUSE; DATA STORAGE SYSTEMS; DEPARTMENT OF DEFENSE; FORMAT RECOGNITION TECHNOLOGIES; INFORMATION EXTRACTION; INFORMATION MANAGEMENT; INFORMATION MODELING; Information Science; Linguistics; LINKAGES; MISSION-BASED FILTERS; ONTOLOGY; OPTIMIZATION; PHOENIX AIR; QOS(QUALITY OF SERVICE); REASONING; ROLE-BASED FILTERS; SEMANTIC DATA EXTRACTION; SEMANTIC REASONING; SEMANTIC SCHEMA MAPPING; SERVICE-ORIENTED ARCHITECTURE; SYMPOSIA
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URL: http://www.dtic.mil/docs/citations/ADA588222
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA588222
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| 12 |
Accelerating Exploitation of Low-grade Intelligence through Semantic Text Processing of Social Media
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In: DTIC (2013)
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QUT Para at TREC 2012 Web Track: Word Associations for Retrieving Web Documents
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In: DTIC (2012)
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| 14 |
Adding a Capability to Extract Sentiment from Text Using HanDles
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In: DTIC (2012)
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| 15 |
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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| 16 |
SAWUS: Siena's Automatic Wikipedia Update System
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In: DTIC (2012)
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| 17 |
CSSG: Learning within NLP Pipelines for Scalable Data Mining and Information Extraction
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In: DTIC (2011)
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| 18 |
Entity List Completion Using Set Expansion Techniques
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In: DTIC (2011)
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| 19 |
Related Entity Finding: University of Waterloo at TREC 2010 Entity Track
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In: DTIC (2010)
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| 20 |
Analysis of Discourse Accent and Discursive Practices I&W
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In: DTIC (2010)
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