tag search result for 'dependency' return
Pablo Gamallo, Caroline Gasperin, Alexandre Agustini, and Gabriel P. Lopes
Syntactic-Based Methods for Measuring Word Similarity
MAUTNER V., MOUCEK R., MOUCEK K., Eds., Text, Speech, and Discourse (TSD-2001),
p. 116--125,
Berlin:Springer Verlag, 2001.
Syntactic-Based Methods for Measuring Word Similarity
MAUTNER V., MOUCEK R., MOUCEK K., Eds., Text, Speech, and Discourse (TSD-2001),
p. 116--125,
Berlin:Springer Verlag, 2001.
Abstract. This paper explores different strategies for extracting similarity relations between words from partially parsed text corpora. The strategies we have analysed do not require supervised training nor semantic information available from general lexical resources. They differ in the amount and the quality of the syntactic contexts against which words are compared. The paper presents in details the notion of syntactic context and how syntactic information could be used to extract semantic regularities of word sequences. Finally, experimental tests with Portuguese corpus demonstrate that similarity measures based on fine-grained and elaborate syntactic contexts perform better than those based on poorly defined contexts.
updated at: 2007/06/12 11:04:03
Gerda Ruge.
Automatic detection of thesaurus relations for information retrieval applications.
In Foundations of Computer Science: Potential - Theory - Cognition, Lecture Notes in Computer Science, volume LNCS 1337,
pp. 499--506,
Springer Verlag, Berlin, Germany,
1997.
Automatic detection of thesaurus relations for information retrieval applications.
In Foundations of Computer Science: Potential - Theory - Cognition, Lecture Notes in Computer Science, volume LNCS 1337,
pp. 499--506,
Springer Verlag, Berlin, Germany,
1997.
Abstract. Is it possible to discover semantic term relations useful for thesauri without any semantic information? Yes, it is. A recent approach for automatic thesaurus construction is based on explicit linguistic knowledge, i.e. a domain independent parser without any semantic component and implicit linguistic knowledge contained in large amounts of real world texts. Such texts include implicitly the linguistic, especially semantic knowledge that the authors needed for formulating their texts. This article explains how implicit semantic knowledge can be transformed to an explicit one. Evaluations of quality and performance of the approach are very encouraging.
'The terms are the searchable items of the system'
'The concept semantically similar subsumes all these thesaurus relations' -> synonymy, hyperonyms, hyponyms, ...
"synonymy" in its strong sense <-> semantically similar
Hearst's method -> 'leads to hyponyms that are not directly related in the hierarchy like "species" and "steatornis oilbird" or
questionable hyponyms like "target" and "airplane".
"semanticlly similar terms have similar definitions in a lexicon."
"terms having many heads and modifiers in common are semantically similar"
'The concept semantically similar subsumes all these thesaurus relations' -> synonymy, hyperonyms, hyponyms, ...
"synonymy" in its strong sense <-> semantically similar
Hearst's method -> 'leads to hyponyms that are not directly related in the hierarchy like "species" and "steatornis oilbird" or
questionable hyponyms like "target" and "airplane".
"semanticlly similar terms have similar definitions in a lexicon."
"terms having many heads and modifiers in common are semantically similar"
updated at: 2007/01/20 17:35:46
Dekang Lin.
Automatic retrieval and clustering of similar words.
In Proceedings of the 17th International Conference on Computational Linguistics and of the 36th Annual Meeting of the Association for Computational Linguistics,
pp. 768-774,
1998.
Automatic retrieval and clustering of similar words.
In Proceedings of the 17th International Conference on Computational Linguistics and of the 36th Annual Meeting of the Association for Computational Linguistics,
pp. 768-774,
1998.
Abstract: Bootstrapping semantics from text is one of the greatest challenges in natural language learning. We first define a word similarity measure based on the distributional pattern of words. The similarity measure allows us to construct a thesaurus using a parsed corpus. We then present a new evaluation methodology for the automatically constructed thesaurus. The evaluation results show that the thesaurus is significantly closer to WordNet than Roget Thesaurus is.
"It was shown in (Dagan et al., 1997) that a similarity-based smoothing
method achieved much better results than backoff smoothing methods in
word sense disambiguation."
"The differences between Hindle and Hindle_r clearly demonstrate that
the use of other types of dependencies in addition to subject and
object relationships is very beneficial."
method achieved much better results than backoff smoothing methods in
word sense disambiguation."
"The differences between Hindle and Hindle_r clearly demonstrate that
the use of other types of dependencies in addition to subject and
object relationships is very beneficial."
updated at: 2007/01/20 17:33:48