| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6902341 | Procedia Computer Science | 2017 | 9 Pages |
Abstract
Hotel booking websites use online ratings and customer feedback to help the customer's decision making process but reviews provide a better insight about the hotel but most travellers don't have the time or patience to read all reviews. This study analyzes the hotel reviews and gives information that ratings might overlook. The reviews and metadata are crawled from website and classified into predefined classes as per some of the common aspects. Then Topic modelling technique (LDA) is applied to identify hidden information and aspects, followed by sentiment analysis on classified sentences and summarization. Finally we discuss results and future work, ultimately building towards Hotel Recommender System.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Nadeem Akhtar, Nashez Zubair, Abhishek Kumar, Tameem Ahmad,