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Automatically Labeling Semantic Classes
"... Systems that automatically discover semantic classes have emerged in part to address the limitations of broad-coverage lexical resources such as WordNet and Cyc. The current state of the art discovers many semantic classes but fails to label their concepts. We propose an algorithm labeling semantic ..."
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Systems that automatically discover semantic classes have emerged in part to address the limitations of broad-coverage lexical resources such as WordNet and Cyc. The current state of the art discovers many semantic classes but fails to label their concepts. We propose an algorithm labeling semantic
Automatically Labeling Semantic Classes
"... Systems that automatically discover semantic classes have emerged in part to address the limitations of broad-coverage lexical resources such as WordNet and Cyc. The current state of the art discovers many semantic classes but fails to label their concepts. We propose an algorithm labeling semantic ..."
Abstract
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Systems that automatically discover semantic classes have emerged in part to address the limitations of broad-coverage lexical resources such as WordNet and Cyc. The current state of the art discovers many semantic classes but fails to label their concepts. We propose an algorithm labeling semantic
Supervised learning of semantic classes for image annotation and retrieval
- IEEE Transactions on Pattern Analysis and Machine Intelligence
, 2007
"... Abstract—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as the group of database images labeled with a common semantic label. It is shown that, by establishing this one-to- ..."
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Cited by 223 (18 self)
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Abstract—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as the group of database images labeled with a common semantic label. It is shown that, by establishing this one
Semantic classes and syntactic ambiguity
- In Proceedings of ARPA Workshop on Human Language Technology
, 1993
"... resnik @ linc.cis.upenn.edu In this paper we propose to define selectional preference and semantic similarity as information-theoretic relationships involving conceptual classes, and we demonstrate the applicability of these definitions to the resolution of syntactic ambiguity. The space of classes ..."
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Cited by 56 (6 self)
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resnik @ linc.cis.upenn.edu In this paper we propose to define selectional preference and semantic similarity as information-theoretic relationships involving conceptual classes, and we demonstrate the applicability of these definitions to the resolution of syntactic ambiguity. The space of classes
Using Semantic Classes as Document Keywords
"... Abstract. Keyphrases are mainly words that capture the main topics of a document. We think that semantic classes can be used as keyphrases for a text. We have developed a semantic class–based WSD system that can tag the words of a text with their semantic class. A method is developed to compare the ..."
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Abstract. Keyphrases are mainly words that capture the main topics of a document. We think that semantic classes can be used as keyphrases for a text. We have developed a semantic class–based WSD system that can tag the words of a text with their semantic class. A method is developed to compare
Semantic Class Induction and Coreference Resolution
- Proc. of the ACL
, 2007
"... This paper examines whether a learningbased coreference resolver can be improved using semantic class knowledge that is automatically acquired from a version of the Penn Treebank in which the noun phrases are labeled with their semantic classes. Experiments on the ACE test data show that a resolver ..."
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Cited by 18 (1 self)
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This paper examines whether a learningbased coreference resolver can be improved using semantic class knowledge that is automatically acquired from a version of the Penn Treebank in which the noun phrases are labeled with their semantic classes. Experiments on the ACE test data show that a resolver
Efficient semantic matching
, 2004
"... We think of Match as an operator which takes two graph-like structures and produces a mapping between semantically related nodes. We concentrate on classifications with tree structures. In semantic matching, correspondences are discovered by translating the natural language labels of nodes into prop ..."
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Cited by 855 (68 self)
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We think of Match as an operator which takes two graph-like structures and produces a mapping between semantically related nodes. We concentrate on classifications with tree structures. In semantic matching, correspondences are discovered by translating the natural language labels of nodes
Probabilistic Latent Semantic Analysis
- In Proc. of Uncertainty in Artificial Intelligence, UAI’99
, 1999
"... Probabilistic Latent Semantic Analysis is a novel statistical technique for the analysis of two--mode and co-occurrence data, which has applications in information retrieval and filtering, natural language processing, machine learning from text, and in related areas. Compared to standard Latent Sema ..."
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Cited by 771 (9 self)
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Semantic Analysis which stems from linear algebra and performs a Singular Value Decomposition of co-occurrence tables, the proposed method is based on a mixture decomposition derived from a latent class model. This results in a more principled approach which has a solid foundation in statistics. In order
Improving Dependency Parsing with Semantic Classes
"... This paper presents the introduction of WordNet semantic classes in a dependency parser, obtaining improvements on the full Penn Treebank for the first time. We tried different combinations of some basic semantic classes and word sense disambiguation algorithms. Our experiments show that selecting t ..."
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Cited by 6 (1 self)
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This paper presents the introduction of WordNet semantic classes in a dependency parser, obtaining improvements on the full Penn Treebank for the first time. We tried different combinations of some basic semantic classes and word sense disambiguation algorithms. Our experiments show that selecting
Probabilistic Latent Semantic Indexing
, 1999
"... Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized ..."
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Cited by 1225 (10 self)
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Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fitted from a training corpus of text documents by a generalization of the Expectation Maximization algorithm, the utilized
Results 1 - 10
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