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Semantic similarity methods in wordNet and their application to information retrieval on the web

Petrakis Evripidis, Voutsakis Epimenidis , Varelas Giannis, Raftopoulou Paraskevi , Evangelos E. Milios

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/9182167E-8BDB-46D9-A98B-525681EB3025
Έτος 2005
Τύπος Περίληψη Δημοσίευσης σε Συνέδριο
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά Giannis Varelas, Paraskevi Raftopoulou, Euripides G.M. Petrakis, Evangelos E. Milios, "Semantic Similarity Methods in WordNet and their Application to Information Retrieval on the Web" , in 7th ACM International Workshop on Web Information and Data Management (WIDM 2005), 2005, pp. 10-16. doi:10.1145/1097047.1097051 https://doi.org/10.1145/1097047.1097051
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Περίληψη

Semantic Similarity relates to computing the similarity between concepts which are not lexicographically similar. We investigate approaches to computing semantic similarity by mapping terms (concepts) to an ontology and by examining their relationships in that ontology. Some of the most popular semantic similarity methods are implemented and evaluated using WordNet as the underlying reference ontology. Building upon the idea of semantic similarity, a novel information retrieval method is also proposed. This method is capable of detecting similarities between documents containing semantically similar but not necessarily lexicographically similar terms. The proposed method has been evaluated in retrieval of images and documents on the Web. The experimental results demonstrated very promising performance improvements over state-of-the-art information retrieval methods.

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