Work

Supervised Methods for Aspect-Based Sentiment Analysis

Year: 2014

Type: conference-paper

Abstract: In this paper, we present our contribution in SemEval2014 ABSA task, some supervised methods for Aspect-Based Sentiment Analysis of restaurant and laptop reviews are proposed, implemented and evaluated.We focus on determining the aspect terms existing in each sentence, finding out their polarities, detecting the categories of the sentence and the polarity of each category.The evaluation results of our proposed methods exhibit a significant improvement in terms of accuracy and f-measure over all four subtasks regarding to the baseline proposed by SemEval organisers.

Source: International Workshop on Semantic Evaluation (SemEval)

DOI: 10.3115/v1/s14-2104

Authors: Hussam Hamdan, Patrice Bellot, Frederic Bechet

Institutions: Centre National de la Recherche Scientifique, Aix-Marseille Université, Laboratoire d’Informatique et Systèmes, Laboratoire d’Informatique Fondamentale de Marseille, OpenEdition Center

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W2251232242

FWCI: 0.775

Cites: 17

Cited by: 14

Related to: 10