This paper presents an application of PageRank, a random-walk model originally devised for ranking Web search results, to ranking WordNet synsets in terms of how strongly they possess a given semantic property. The semantic properties we use for exemplifying the approach are positivity and negativity, two properties of central importance in sentiment analysis. The rationale of applying PageRank to detecting the semantic properties of synsets lies in the fact that the space of WordNet synsets may be seen as a graph, in which synsets are connectedthrough the binary relation
PageRanking WordNet Synsets: an application to opinion mining
Esuli A;Sebastiani F
2007
Abstract
This paper presents an application of PageRank, a random-walk model originally devised for ranking Web search results, to ranking WordNet synsets in terms of how strongly they possess a given semantic property. The semantic properties we use for exemplifying the approach are positivity and negativity, two properties of central importance in sentiment analysis. The rationale of applying PageRank to detecting the semantic properties of synsets lies in the fact that the space of WordNet synsets may be seen as a graph, in which synsets are connectedthrough the binary relationFile in questo prodotto:
File | Dimensione | Formato | |
---|---|---|---|
prod_160877-doc_132025.pdf
solo utenti autorizzati
Descrizione: PageRanking WordNet Synsets: an application to opinion mining
Dimensione
166.19 kB
Formato
Adobe PDF
|
166.19 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.