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Frequency: Monthly
ISSN: 1549-3636 (Print)
ISSN: 1552-6607 (Online)
Research Article Open Access

RHALSA: Ranking Hotels using Aspect Level Sentiment Analysis

Nibedita Panigrahi1 and Asha T1
  • 1 Bangalore Institute of Technology, India

Abstract

Opinion play a vital role which impacts the business in large extent. Users by-and-large depend on the reviews of others to avail the services. Online hotel bookings are becoming popular because of mobile applications being used on smart phones for placing the bookings from far away in advance along with the access to their reviews on different aspects. In this work, we present a data mining algorithm to rank the hotels based on the reviews provided by the users using aspect level sentiment analysis. The proposed Ranking Hotels using Aspect Level Sentiment Analysis (RHALSA) algorithm is evaluated conducting experiments on Tripadvisor data set to demonstrate its adequacy.

Journal of Computer Science
Volume 14 No. 11, 2018, 1512-1520

DOI: https://doi.org/10.3844/jcssp.2018.1512.1520

Submitted On: 4 May 2018 Published On: 15 November 2018

How to Cite: Panigrahi, N. & T, A. (2018). RHALSA: Ranking Hotels using Aspect Level Sentiment Analysis. Journal of Computer Science, 14(11), 1512-1520. https://doi.org/10.3844/jcssp.2018.1512.1520

Open AccessCopyright: © 2018 Nibedita Panigrahi and Asha T. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

  • Aspects
  • Data Mining
  • Hotel Reviews
  • Natural Language Processing
  • Opinion Mining
  • Ranking
  • Sentiment Analysis