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Relevance Feedback based on Constrained Clustering: FDU at TREC 09
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In: DTIC (2009)
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| 2 |
Linking Semantic and Knowledge Representations in a Multi-Domain Dialogue System
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In: DTIC (2007)
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| 3 |
Techniques for Automatically Generating Biographical Summaries from News Articles
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In: DTIC (2007)
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| 4 |
Headline Generation for Written and Broadcast News
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In: DTIC (2005)
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| 5 |
Stochastic Language Generation in a Dialogue System: Toward a Domain Independent Generator
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In: DTIC (2004)
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BASE
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| 6 |
Advanced Capabilities for Evidence Extraction (ACEE)
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In: DTIC AND NTIS (2004)
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| 7 |
Development and Evaluation of a Korean Treebank and its Application to NLP
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In: DTIC (2002)
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| 8 |
The Bible, Truth, and Multilingual OCR Evaluation
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In: DTIC (1998)
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| 11 |
TMSS Parsing Test, MIL-M-9977J, Appendix G, Loading Procedures Checklists.
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In: DTIC AND NTIS (1994)
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BASE
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| 12 |
TMSS Parsing Test, MIL-M-9977J, Appendix H, Integrated Combat Turnaround Procedures Checklist.
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In: DTIC AND NTIS (1994)
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| 13 |
Using Case-Based Reasoning in Natural Language Processing
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In: DTIC AND NTIS (1993)
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| 14 |
Domain and Language Evaluation Results
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In: DTIC (1993)
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Abstract:
The Fifth Message Understanding Conference (MUC-5) focused on the task of data extraction for two distinctly different applications, one within the domain of joint ventures (JV) and the other within the domain of microelectronics (ME) . For each application, the task could be performed in either English and/or Japanese, giving four combinations : English Joint Ventures, Japanese Joint Ventures, English Microelectronics, and Japanese Microelectronics . Interpreting the evaluation results across domains and within a single domain between languages is affected d by a number of factors. Differences in task focus, complexity, and domain technicality make it impossible to apply inferential statistics between domains . In addition, even though the task and the template design were the same across languages within a single domain, differences in the types of text sources for each language and accompanying variations in template fills and fill rules by language also make it impossible to apply inferential statistics between the language pairs . Moreover, there is considerable variation in the participants' level of effort and funding, and not all of the participants worked in multiple languages and/or multiple domains . In light of these factors, I will present descriptive statistics comparing error per response fill to address the following questions : (1) For both languages, what is the performance difference between domains? (2) Between domains, what are performance differences for the single shared object and for unattempted slots? (3) For both domains, what is the performance difference between languages? (4) For a single domain, what are representative differences at object and slot levels between English and Japanese? The discussion of domain and language difference s will center upon general factors that influence performance in information extraction.
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Keyword:
*DATA PROCESSING; *ENGLISH LANGUAGE; *INFORMATION RETRIEVAL; *MICROELECTRONICS; *STATISTICS; Electrical and Electronic Equipment; EXTRACTION; FILLERS; Information Science; JAPAN; LANGUAGE; Linguistics; SHARING; SLOTS; Statistics and Probability; TEMPLATES; TEST AND EVALUATION
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA460578
http://www.dtic.mil/docs/citations/ADA460578
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| 15 |
Tipster Shogun System (Joint GE-CMU): MUC-4 Test Results and Analysis
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In: DTIC (1992)
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GE-CMU: Description of the Tipster/Shogun System as Used for MUC-4
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In: DTIC (1992)
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| 18 |
BBN HARC and DELPHI Results on the ATIS Benchmarks - February 1991
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In: DTIC (1991)
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| 20 |
Augmented Role Filling Capabilities for Semantic Interpretation of Spoken Language
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In: DTIC (1991)
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