Identification of Latent Aspects Using Bayesian Non-Parametric Models

11 Pages Posted: 9 Mar 2018

See all articles by K Nandhini Devi

K Nandhini Devi

Sona College of Technology, Department of Computer Science and Engineering, Students

D Vidyabharati

Sona College of Technology

Date Written: November 15, 2017

Abstract

Sentiment analysis is increasingly viewed as a vital task both from an academic and a commercial standpoint. The majority of current approaches, however, attempt to detect the overall polarity of a sentence, paragraph, or text span, regardless of the entities (e.g., laptops, restaurants) and their aspects (e.g., battery, screen; food, service) are mentioned. By contrast, this task is concerned with aspect based sentiment analysis (ABSA), where the goal is to identify the aspects of given target entities and the sentiment expressed towards each aspect. Although, it is mandatory to evaluate both the positive and negative reviews of the customer. Since the analysis of negative review will help to improve the business specification. This system is mainly about evaluating reviews for specific entities of any products based on the three slots: aspect categories, opinion target expressions, and polarity classification. Aspect category is to identify an entity E and attribute A pair from which the reviews are expressed. Opinion target expressions are based on customer review for each product. Polarity classification is used to identify or express the positive and negative reviews of the product. Also the project helps to infer the hidden latent topics using a Bayesian Non Parametric model. The existing models failed to provide the Inter-Dependency between aspects based analysis & over-all ratings. Initially this phase is all about finding the aspect based sentiment analysis using Naive Bayes algorithm.

Keywords: Aspect based sentiment analysis, Naïve Bayes algorithm, Latent topics

Suggested Citation

Nandhini Devi, K and Vidyabharati, D, Identification of Latent Aspects Using Bayesian Non-Parametric Models (November 15, 2017). Proceedings of the International Conference on Intelligent Computing Systems (ICICS 2017 – Dec 15th - 16th 2017) organized by Sona College of Technology, Salem, Tamilnadu, India, Available at SSRN: https://ssrn.com/abstract=3134280 or http://dx.doi.org/10.2139/ssrn.3134280

K Nandhini Devi (Contact Author)

Sona College of Technology, Department of Computer Science and Engineering, Students ( email )

Junction Main Road
Suramangalam
Salem, Tamil Nadu 636005
India

D Vidyabharati

Sona College of Technology ( email )

Junction Main Road
Suramangalam
Salem, Tamil Nadu 636005
India

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