Semantic web-based approaches and computational intelligence can be merged in order to gel useful tools for several data mining issues. In this work a web-based tagging process followed by a validation step is carried to tag Word Net adjectives with positive, neutral or negative moods. This tagged Word Net is used to define a semantic metric for text documents clustering. Experimental results on movie reviews prove that the introduced semantically oriented metric is extremely fast and gives improved results with respect to the classical frequency based text mining metric from the accuracy point of view.

Semantic Oriented Clustering of Documents

GASTALDO, PAOLO;ZUNINO, RODOLFO
2011-01-01

Abstract

Semantic web-based approaches and computational intelligence can be merged in order to gel useful tools for several data mining issues. In this work a web-based tagging process followed by a validation step is carried to tag Word Net adjectives with positive, neutral or negative moods. This tagged Word Net is used to define a semantic metric for text documents clustering. Experimental results on movie reviews prove that the introduced semantically oriented metric is extremely fast and gives improved results with respect to the classical frequency based text mining metric from the accuracy point of view.
2011
9783642211102
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/376379
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 4
social impact