V3: Unsupervised Generation of Domain Aspect Terms for Aspect Based Sentiment Analysis | Zendy

Aitor García Pablos | Zendy; Montse Cuadros | Zendy; Germán Rigau | Zendy

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V3: Unsupervised Generation of Domain Aspect Terms for Aspect Based Sentiment Analysis

Author(s) -

Aitor García Pablos,

Montse Cuadros,

Germán Rigau

Publication year - 2014

Publication title -

proceedings of the 16th international workshop on semantic evaluation (semeval-2022)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.3115/v1/s14-2148

Subject(s) - computer science , domain (mathematical analysis) , sentiment analysis , natural language processing , artificial intelligence , semeval , task (project management) , domain analysis , information retrieval , programming language , software , mathematics , engineering , mathematical analysis , software construction , systems engineering , software system

This paper presents V3, an unsupervised system for aspect-based Sentiment Analysis when evaluated on the SemEval 2014 Task 4. V3 focuses on generating a list of aspect terms for a new domain using a collection of raw texts from the domain. We also implement a very basic approach to classify the aspect terms into categories and assign polarities to them.

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