@inproceedings{8c1cc41211b24446966522dd79e47710,
title = "Hotel recommendation system based on review and context information: A Collaborative Filtering approach",
abstract = "Due to the increment of different formats of online expressions such as reviews, ratings, and recommendation, it is getting more difficult to identify users' preferences toward the products. A large number of reviews can be generated and diffused by online users in travel booking websites. A set of Recommendation Systems (RSs) has emerged to help consumers to filter items based on their preferences. The Collaborative Filtering (CF) based approach is one of the most popular techniques of the RS; however, it also suffers from several fundamental problems such as data sparsity, cold start, shortage, and rating bias. This study proposes a context-aware hotel recommendation (CAPH) approach; using the context-aware information to provide personalized hotel recommendation system. This research considers recommending hotels based on the hotel features and traveler's type. Experimental data is collected from Tripadvior.com during the period of 2015 to 2016. The evaluations of system accuracy will be conducted and then compared with the user-based/item-based CF model.",
keywords = "Collaborative Filtering, Context analysis, Recommender system",
author = "Hu, {Ya Han} and Lee, {Pei Ju} and Kuanchin Chen and Tarn, {J. Michael} and Dang, {Duyen Vi}",
year = "2016",
language = "???core.languages.en_GB???",
series = "Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedings",
publisher = "Pacific Asia Conference on Information Systems",
booktitle = "Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedings",
note = "20th Pacific Asia Conference on Information Systems, PACIS 2016 ; Conference date: 27-06-2016 Through 01-07-2016",
}