Document Detail


Structural semantic interconnections: a knowledge-based approach to word sense disambiguation.
MedLine Citation:
PMID:  16013755     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Word Sense Disambiguation (WSD) is traditionally considered an Al-hard problem. A break-through in this field would have a significant impact on many relevant Web-based applications, such as Web information retrieval, improved access to Web services, information extraction, etc. Early approaches to WSD, based on knowledge representation techniques, have been replaced in the past few years by more robust machine learning and statistical techniques. The results of recent comparative evaluations of WSD systems, however, show that these methods have inherent limitations. On the other hand, the increasing availability of large-scale, rich lexical knowledge resources seems to provide new challenges to knowledge-based approaches. In this paper, we present a method, called structural semantic interconnections (SSI), which creates structural specifications of the possible senses for each word in a context and selects the best hypothesis according to a grammar G, describing relations between sense specifications. Sense specifications are created from several available lexical resources that we integrated in part manually, in part with the help of automatic procedures. The SSI algorithm has been applied to different semantic disambiguation problems, like automatic ontology population, disambiguation of sentences in generic texts, disambiguation of words in glossary definitions. Evaluation experiments have been performed on specific knowledge domains (e.g., tourism, computer networks, enterprise interoperability), as well as on standard disambiguation test sets.
Authors:
Roberto Navigli; Paola Velardi
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Publication Detail:
Type:  Comparative Study; Evaluation Studies; Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  IEEE transactions on pattern analysis and machine intelligence     Volume:  27     ISSN:  0162-8828     ISO Abbreviation:  IEEE Trans Pattern Anal Mach Intell     Publication Date:  2005 Jul 
Date Detail:
Created Date:  2005-07-14     Completed Date:  2005-08-11     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  9885960     Medline TA:  IEEE Trans Pattern Anal Mach Intell     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1075-86     Citation Subset:  IM    
Affiliation:
Dipartimento di Informatica, Università of Roma La Sapienza, via Salaria 113, 00198 Roma, Italy. navigli@di.uniroma.it
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Artificial Intelligence*
Cluster Analysis
Computer Simulation
Dictionaries as Topic
Information Storage and Retrieval / methods*
Models, Statistical*
Natural Language Processing*
Numerical Analysis, Computer-Assisted
Pattern Recognition, Automated / methods*
Sequence Alignment / methods
Sequence Analysis / methods*
Vocabulary, Controlled

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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