Elsevier

Procedia Technology

Volume 11, 2013, Pages 495-501
Procedia Technology

Integration of Sentiment Analysis into Customer Relational Model: The Importance of Feature Ontology and Synonym

https://doi.org/10.1016/j.protcy.2013.12.220Get rights and content
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open access

Abstract

Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction about their products. Opinion mining is used to capture customer reviews and separated this review into subjective expressions (sentiment word) and objective expressions (no sentiment word). This paper proposes a novel, multi-dimensional model for opinion mining, which integrates customers’ characteristics and their opinion about any products. The model captures subjective expression from product reviews and transfers to fact table before representing in multi-dimensions named as customers, products, time and location. Data warehouse techniques such as OLAP and Data Cubes were used to analyze opinionated sentences. A comprehensive way to calculate customers’ orientation on products’ features and attributes are presented in this paper.

Keywords

opinion mining
sentiment analysis
feature ontology
structured data
unstructured data
subjective expression
polarity

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Selection and peer-review under responsibility of the Faculty of Information Science & Technology, Universiti Kebangsaan Malaysia.