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Robust and Efficient Anti-Phishing Techniques
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In: DTIC (2012)
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| 2 |
Fighting for Intelligence: The Design of Intelligence-Led Operations
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In: DTIC (2008)
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| 3 |
Fast Unconstrained Audio Search in Numerous Human Languages
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In: DTIC (2007)
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| 4 |
Effectively Using Syntax for Recognizing False Entailment
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In: DTIC (2006)
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| 5 |
Sparse Forward-Backward for Fast Training of Conditional Random Fields
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In: DTIC (2006)
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| 6 |
TREC2001 Question-Answer, Web and Cross Language Experiments Using PIRCS
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In: DTIC (2006)
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| 7 |
Intelligence Analyst Associate (IAA) - CYC Knowledge Extraction
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In: DTIC AND NTIS (2003)
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| 10 |
Evaluating Question-Answering Techniques in Chinese
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In: DTIC (2001)
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| 11 |
Optimal Allocation of Distributed Resources Using Fuzzy Logic and a Genetic Algorithm
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In: DTIC (2000)
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| 12 |
Efficient Algorithms for Speech Recognition.
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In: DTIC AND NTIS (1996)
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| 13 |
Situation, Domain, and Coherence: Toward a Pragmatic Psychology of Understanding.
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In: DTIC AND NTIS (1996)
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| 14 |
Recent Experiments with INQUERY
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In: DTIC (1995)
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Abstract:
Past TREC experiments by the University of Massachusetts have focused primarily on ad hoc query creation. Substantial effort was directed towards automatically translating TREC topics into queries using a set of simple heuristics and query expansion. Less emphasis was placed on the routing task although results were generally good. The Spanish experiments in TREC-3 concentrated on simple indexing sophisticated stemming and simple methods of creating queries. The TREC-4 experiments were a departure from the past. The ad hoc experiments involved "fine tuning" existing approaches and modifications to the INQUERY term weighting algorithm. However, much of the research focus in TREC-4 was on the routing, Spanish, and collection merging experiments. These tracks more closely match our broader research interests in document routing document filtering distributed IR, and multilingual retrieval. The University of Massachusetts experiments were conducted with version 3.0 of the INQUERY information retrieval system. INQUERY is based on the Bayesian inference network retrieval model. It is described elsewhere [7, 5, 12, 11], so this paper focuses on relevant differences to the previously published algorithms. ; Presented at the Text Retrieval Conference "TREC-4" (4th) Held at Gaithersburg, MD on 1-3 Nov 1995.
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Keyword:
*INFORMATION RETRIEVAL; ALGORITHMS; HEURISTIC METHODS; INDEXES; Information Science; INTERROGATION; Linguistics; Numerical Mathematics; ROUTING; SPANISH LANGUAGE; TUNING; WEIGHTING FUNCTIONS
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA470554
http://www.dtic.mil/docs/citations/ADA470554
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| 15 |
Semiautomatic Deabbreviation of Source Programs
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In: DTIC AND NTIS (1994)
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| 16 |
Using Multiple Adaptively-Weighted Strategies for the Resolution of Demonstratives
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In: DTIC AND NTIS (1993)
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| 17 |
SRI International: Description of the Tacitus System as Used for MUC-3
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In: DTIC (1991)
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| 19 |
The MIT Summit Speech Recognition System: A Progress Report
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In: DTIC (1989)
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| 20 |
A Model for Integrating a Job-Aiding, Training, and Performance Assessment System--a Preliminary Concept Paper.
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In: DTIC AND NTIS (1988)
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