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检索条件"任意字段=Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing"
947 条 记 录,以下是901-910 订阅
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Chinese whispers: an efficient graph clustering algorithm and its application to natural language processing problems  1
Chinese whispers: an efficient graph clustering algorithm an...
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proceedings of the first workshop on graph based methods for natural language processing
作者: Chris Biemann University of Leipzig Leipzig Germany
We introduce Chinese Whispers, a randomized graph-clustering algorithm, which is time-linear in the number of edges. After a detailed definition of the algorithm and a discussion of its strengths and weaknesses, the p...
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Study of Some Distance Measures for language and Encoding Identification
Study of Some Distance Measures for Language and Encoding Id...
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2006 workshop on Linguistic Distances, held in conjunction of COLING ACL 2006
作者: Singh, Anil Kumar Language Technologies Research Centre International Institute of Information Technology Hyderabad India
To determine how close two language models (e.g., n-grams models) are, we can use several distance measures. If we can represent the models as distributions, then the similarity is basically the similarity of distribu... 详细信息
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Generative content models for structural analysis of medical abstracts
Generative content models for structural analysis of medical...
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HLT-NAACL 2006 workshop on Linking natural language processing and Biology: Towards Deeper Biological Literature Analysis, BioNLP 2006
作者: Lin, Jimmy Karakos, Damianos Demner-Fushman, Dina Khudanpur, Sanjeev College of Information Studies University of Maryland College ParkMD20742 United States Institute for Advanced Computer Studies University of Maryland College ParkMD20742 United States Center for Language and Speech Processing Johns Hopkins University BaltimoreMD21218 United States
The ability to accurately model the content structure of text is important for many natural language processing applications. This paper describes experiments with generative models for analyzing the discourse structu... 详细信息
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graph-based generalized latent semantic analysis for document representation  1
Graph-based generalized latent semantic analysis for documen...
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proceedings of the first workshop on graph based methods for natural language processing
作者: Irina Matveeva Gina-Anne Levow University of Chicago Chicago IL
Document indexing and representation of term-document relations are very important for document clustering and retrieval. In this paper, we combine a graph-based dimensionality reduction method with a corpus-based ass...
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Learning of graph-based question answering rules  1
Learning of graph-based question answering rules
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proceedings of the first workshop on graph based methods for natural language processing
作者: Diego Mollá Macquarie University Sydney Australia
In this paper we present a graph-based approach to question answering. The method assumes a graph representation of question sentences and text sentences. Question answering rules are automatically learnt from a train...
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graph-based text representation for novelty detection  1
Graph-based text representation for novelty detection
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proceedings of the first workshop on graph based methods for natural language processing
作者: Michael Gamon Microsoft Research Redmond WA
We discuss several feature sets for novelty detection at the sentence level, using the data and procedure established in task 2 of the TREC 2004 novelty track. In particular, we investigate feature sets derived from g...
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graph-based methods for language processing and information retrieval
Graph-based methods for language processing and information ...
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IEEE Spoken language Technology workshop
作者: Dragomir R. Radev University of Michigan USA
Summary form only given. A number of problems in information retrieval and natural language processing can be approached using graph theory. Some representative examples in IR include Brin and Page's Pagerank and ... 详细信息
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Seeing stars when there aren't many stars: graph-based semi-supervised learning for sentiment categorization  1
Seeing stars when there aren't many stars: graph-based semi-...
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proceedings of the first workshop on graph based methods for natural language processing
作者: Andrew B. Goldberg Xiaojin Zhu University of Wisconsin-Madison Madison W.I.
We present a graph-based semi-supervised learning algorithm to address the sentiment analysis task of rating inference. Given a set of documents (e.g., movie reviews) and accompanying ratings (e.g., "4 stars"...
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A study of two graph algorithms in topic-driven summarization  1
A study of two graph algorithms in topic-driven summarizatio...
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proceedings of the first workshop on graph based methods for natural language processing
作者: Vivi Nastase Stan Szpakowicz University of Ottawa Ottawa Canada University of Ottawa Ottawa Canada and Polish Academy of Sciences Warsaw Poland
We study how two graph algorithms apply to topic-driven summarization in the scope of Document Understanding Conferences. The DUC 2005 and 2006 tasks were to summarize into 250 words a collection of documents on a top...
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Widening the NLP pipeline for spoken language processing
Widening the NLP pipeline for spoken language processing
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IEEE Spoken language Technology workshop
作者: Srinivas Bangalore AT&T Labs - Research
Summary form only given. A typical text-based natural language application (eg. machine translation, summarization, information extraction) consists of a pipeline of preprocessing steps such as tokenization, stemming,... 详细信息
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