A Novel Aspect Based Framework for Tourism Sector with Improvised Aspect and Opinion Mining Algorithm

A Novel Aspect Based Framework for Tourism Sector with Improvised Aspect and Opinion Mining Algorithm

Vishal Bhatnagar, Mahima Goyal, Mohammad Anayat Hussain
Copyright: © 2022 |Pages: 15
DOI: 10.4018/978-1-6684-6303-1.ch017
OnDemand:
(Individual Chapters)
Available
$37.50
Current Special Offers
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

With the growth of e-commerce web sites, the demand of writing reviews on these portals have gained huge popularity. This huge data must be mined to analyze the opinion and for making better decisions in different domains. In this paper, we have proposed an aspect based opinion mining algorithm for the tourism domain. It first determines the aspects, and then extracts the opinion words related to the aspects. The opinion words are provided a score based on the Senti-Wordnet and the final score of each aspect is calculated by the summation of the scores of the opinions. The final score is visualized depicting ranking of scores of different aspects for different hotels.
Chapter Preview
Top

Bhatnagar (2010, 2013), Acharjee (2013), and Radhwan (2015) reviewed the different data mining techniques for data analysis. The method of capturing market intelligence has been shown by Li (2013). Ripon et al. (2016) found different automated machine learning techniques and compared them. Opinion mining refers to analyzing of different sentiments, opinions from different product reviews and services. Pang and Lee (2008) discussed different techniques of opinion mining in their book. The term ’opinion mining’ and ‘sentiment analysis’ can be used interchangeably as they both have the same meanings. It can be categorized into three levels- Document Level, Sentence Level and Aspect Level.

Complete Chapter List

Search this Book:
Reset