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Hits 61 – 80 of 411

61
TIACRITIS System and Textbook: Learning Intelligence Analysis through Practice
In: DTIC (2010)
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62
RMIT University at TREC 2009: Web Track
In: DTIC (2009)
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63
A Novel Framework for Related Entities Finding: ICTNET at TREC 2009 Entity Track
In: DTIC (2009)
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64
Recognizing Connotative Meaning in Military Chat Communications
In: DTIC (2009)
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65
Metacognitive Awareness versus Linguistic Politeness: Expressions of Confusion in Tutorial Dialogues
In: DTIC (2009)
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66
Relevance Feedback based on Constrained Clustering: FDU at TREC 09
In: DTIC (2009)
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67
Translation Memory Technology Assessment
In: DTIC (2009)
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68
A Journey in Entity Related Retrieval for TREC 2009
In: DTIC (2009)
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69
ICTNET at Web Track 2009 Diversity task
In: DTIC (2009)
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70
Lucene for n-grams using the ClueWeb Collection
In: DTIC (2009)
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71
BIT at TREC 2009 Faceted Blog Distillation Task
In: DTIC (2009)
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72
Recovering Asynchronous Watermark Tones from Speech
In: DTIC (2009)
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73
Sparse Matrix Factorization: Applications to Latent Semantic Indexing
In: DTIC (2009)
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74
IRRA at TREC 2009: Index Term Weighting based on Divergence From Independence Model
In: DTIC (2009)
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75
Semantic Search
In: DTIC (2009)
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76
Delft University at the TREC 2009 Entity Track: Ranking Wikipedia Entities
In: DTIC (2009)
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77
POSTECH at TREC 2009 Blog Track: Top Stories Identification
In: DTIC (2009)
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78
Entity Retrieval by Hierarchical Relevance Model, Exploiting the Structure of Tables and Learning Homepage Classifiers
In: DTIC (2009)
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79
University of Padua at TREC 2009: Relevance Feedback Track
In: DTIC (2009)
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80
Related Entity Finding Based on Co-Occurrence
In: DTIC (2009)
Abstract: We report on experiments for the Related Entity Finding task in which we focus on only using Wikipedia as a target corpus in which to identify (related) entitities. Our approach is based on co-occurrences between the source entity and potential target entities. We observe improvements in performance when a context-independent co-occurrence model is combined with context-dependent co-occurrence models in which we stress the importance of the expected relation between source and target entity. Applying type filtering yields further improvements results. ; Proceedings of the Text REtrieval Conference (18th), TREC 2009, held in Gaithersburg, Maryland, 17-20 Nov 2009. 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).
Keyword: *RANKING; *STATISTICAL PROCESSES; *TEXT PROCESSING; COMPUTATIONAL LINGUISTICS; Computer Programming and Software; Cybernetics; FOREIGN REPORTS; Information Science; INTERNET; NATURAL LANGUAGE; NETHERLANDS; RELATIONSHIPS; SYMPOSIA; WIKIPEDIA; WORD ASSOCIATION
URL: http://www.dtic.mil/docs/citations/ADA517706
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA517706
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