Title :

A Word Sense Disambiguation Method for Feature Level Sentiment Analysis

Author(s) :

Farooq, Umar [Auteur]
Prasad Dhamala, Tej [Auteur]
Décision et Information pour les Systèmes de Production [DISP]
Nongaillard, Antoine [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ouzrout, Yacine [Auteur]
Décision et Information pour les Systèmes de Production [DISP]
Qadir, Muhammad Abdul [Auteur]

Conference title :

9th IEEE International Conference on Software, Knowledge, Information Management & Applications (SKIMA 2015)

City :

Kathmandu

Country :

Népal

Start date of the conference :

2015-12

English keyword(s) :

Contextual Polarity
Sentiment Analysis
Word Sense Disambiguation

HAL domain(s) :

Informatique [cs]
Informatique [cs]/Traitement du texte et du document

English abstract : [en]

Sentiment analysis is an automatic method used to determine that the opinion of a person about a subject is positive or negative. One of the most important tasks in sentiment analysis is to disambiguate the sense of words ...
Show more >Sentiment analysis is an automatic method used to determine that the opinion of a person about a subject is positive or negative. One of the most important tasks in sentiment analysis is to disambiguate the sense of words according to context. Most errors in sentiment analysis are because of improper sense disambiguation. Few methods for this purpose have been proposed in literature. However, they are not able to properly determine the context of word in a sentence. In addition, the lexicon dictionaries used by these methods lack word senses and also do not provide a context matching technique. These issues need to be addressed in order to improve the performance of sentiment analysis so that it can be used by customers and manufacturers for decision making. In this paper, we propose a feature level sentiment analysis system, which produces a summary of opinions about product features. A word sense disambiguation method is introduced which accurately determines the sense of a word within a context while determining the polarity. In addition, a heuristic based method is proposed in order to determine the text where opinion about a product feature is expressed. The results show that the proposed methods achieve better accuracy than existing methods.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL