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81
Automatic Extraction of Causal Relations from Natural Language Texts: A Comprehensive Survey ...
Asghar, Nabiha. - : arXiv, 2016
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82
On Appropriate Selection of Fuzzy Aggregation Operators in Medical Decision Support System ...
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83
Distributional semantics beyond words: Supervised learning of analogy and paraphrase ...
Turney, Peter D.. - : arXiv, 2013
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84
WNtags: A Web-Based Tool For Image Labeling And Retrieval With Lexical Ontologies ...
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85
Organizing Linked Data Quality Related Methods ...
Martin, Philippe A.. - : arXiv, 2013
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86
The automatic creation of concept maps from documents written using morphologically rich languages ...
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87
Pbm: A new dataset for blog mining ...
Aziz, Mehwish; Rafi, Muhammad. - : arXiv, 2012
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88
Content-based Text Categorization using Wikitology ...
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89
Artex is AnotheR TEXt summarizer ...
Torres-Moreno, Juan-Manuel. - : arXiv, 2012
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90
Opinion Mining for Relating Subjective Expressions and Annual Earnings in US Financial Statements ...
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91
Concrete Sentence Spaces for Compositional Distributional Models of Meaning ...
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92
Expressing Implicit Semantic Relations without Supervision ...
Turney, Peter D.. - : arXiv, 2006
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93
Sur le statut référentiel des entités nommées ...
Poibeau, Thierry. - : arXiv, 2005
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94
Semantic filtering by inference on domain knowledge in spoken dialogue systems ...
Ballim, Afzal; Pallotta, Vincenzo. - : arXiv, 2004
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95
Acquiring Lexical Paraphrases from a Single Corpus ...
Glickman, Oren; Dagan, Ido. - : arXiv, 2003
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96
Bayesian Information Extraction Network ...
Peshkin, Leonid; Pfeffer, Avi. - : arXiv, 2003
Abstract: Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs are applicable to probabilistic language modeling. To demonstrate the potential of DBNs for natural language processing, we employ a DBN in an information extraction task. We show how to assemble wealth of emerging linguistic instruments for shallow parsing, syntactic and semantic tagging, morphological decomposition, named entity recognition etc. in order to incrementally build a robust information extraction system. Our method outperforms previously published results on an established benchmark domain. ... : 6 pages ...
Keyword: Artificial Intelligence cs.AI; C.1.3; I.5.1; I.7.2; I.2.7; Computation and Language cs.CL; FOS Computer and information sciences; Information Retrieval cs.IR
URL: https://arxiv.org/abs/cs/0306039
https://dx.doi.org/10.48550/arxiv.cs/0306039
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