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HOTEL RECOMMENDATION SYSTEM USING HYBRID TECHNIQUE
2020
International Journal of Advanced Research in Computer Science
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In addition, increasing the accuracy in predicting the appropriate items suggested to the user's preferences is one of the main challenges faced in these systems. ...
Collaborative filtering may be a set of technologies that predict which items during a set of information a specific customer will like supported the preferences of many people. ...
A large number of reviews can be generated and diffused by online users in travel booking websites. ...
doi:10.26483/ijarcs.v11i3.6529
fatcat:eoyfkazqcfgi7fkish6dajosau
How Online Reviews in a Year Predict Online Sales in the Next on Expedia.com + Agoda.com + Hotels.com? A Panel Study of Hotels
2019
2019 5th International Conference on Information Management (ICIM)
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This paper investigates how ratings, titles as well as descriptions of online reviews predict online sales. ...
The use of positive words in titles was positively related to sales for luxury hotels but had a negative association for budget hotels. ...
ACKNOWLEDGMENT The first author thanks Dr Alton Chua for his supervision of the PhD dissertation, which eventually inspired this work. ...
doi:10.1109/infoman.2019.8714708
fatcat:wahd6omkxjdvvj7ctyyr24drbq
Stripping customers' feedback on hotels through data mining: The case of Las Vegas Strip
2017
Tourism Management Perspectives
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89 Concluding, the main goals and contributions of this study are as follows: 90 Creating a model that predicts the review score based on quantitative features of the 91 user/reviewer and the hotel, ...
Influence of "Nr. Rooms" on TripAdvisor score. displays the effect of the number of stars of the hotel on TripAdvisor score. ...
doi:10.1016/j.tmp.2017.04.003
fatcat:4w7cuztmuvak3lgdmllzsjtoie
Trust Based Novel Recommendation Regularized with Item Ratings
2017
International Journal for Research in Applied Science and Engineering Technology
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Here we use a scale to reflect the quality of product where user selects the number which is taken into consideration. ...
networking to connect people in a commodity so that people can get to know about a product or place in detail by the information shared about it and the user can sort out things according to their needs ...
If the user is not able to find their friend's rating/review for a hotel, mining process helps the user to view his/her friends of friends review.
VI. ...
doi:10.22214/ijraset.2017.4086
fatcat:lzwdh4eimzaa3junt2yng6i7lu
Crime Prediction Using Hotel Reviews?
2019
2019 European Intelligence and Security Informatics Conference (EISIC)
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More research and domain knowledge are needed to establish the strength of hotel reviews as a proxy for crime prediction. ...
One possible explanation for this counterintuitive finding that the review data are not mapped against specific crime types, and thus the crime data capture mostly police visibility on the site. ...
Hotel reviews are influenced by the perception of how users feel about the hotel, the time and location the review published, and the ability of the user to recall and observe events during their stay. ...
doi:10.1109/eisic49498.2019.9108861
dblp:conf/eisic/KostakosRLO19
fatcat:tq5ij2hccfhxzhyw4zdjezcqmi
Social Influence Bias in Online Ratings: A Field Experiment
2016
Social Science Research Network
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Furthermore, we are able to exclude any brag-or-moan effect: the behavior of frequent reviewers, on average, is not statistically different from the behavior of consumers who have never posted ratings ...
of ratings: if there are biases in how users review products and services, online ratings 1 ...
We gratefully acknowledge the research assistance of students of the Master in Tourism Economics and Management, University of Bologna, Rimini Campus and of Riccardo Tonielli. ...
doi:10.2139/ssrn.2737992
fatcat:ioinq4gpi5h65ai3wxrahmtnga
Recommendation System: State of the Art Approach
2015
International Journal of Computer Applications
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Certainly, recommendation systems have an assortment of properties that may entail experiences of user such as user preference, prediction accuracy, confidence, trust, etc. ...
In this paper we present a categorical reassess of the field of recommender systems and Approaches for Evaluation of Recommendation System to propose the recommendation method that would further help to ...
Higher online transaction is one of the biggest effects of easier Internet usage in most of the countries. ...
doi:10.5120/21281-4200
fatcat:bpkrrywowrfjfhot45jlo5ps6u
Application of Machine Learning in the Hotel Industry: A Critical Review
2020
Journal of Association of Arab Universities for Tourism and Hospitality
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Therefore, the purpose of this study is to give insights on the role of ML and its integrated technologies in the hotel industry. ...
community knowledge and awareness on machine learning in the hotel industry. ...
The online review patterns of users from developed and developing countries are different. ...
doi:10.21608/jaauth.2020.38784.1060
fatcat:qqa3k4qkdra73a33o75yyqvhvm
User-Centric vs. System-Centric Evaluation of Recommender Systems
[chapter]
2013
Lecture Notes in Computer Science
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We discuss two studies that have adopted a system-centric approach using data from 210000 users, and a user-centric approach involving 240 users interacting with an online hotel booking service. ...
Recommender Systems (RSs) aim at helping users search large amounts of contents and identify more effectively the items (products or services) that are likely to be more useful or attractive. ...
When watching a list of hotels previously filtered according to accommodation characteristics, the user is offered an additional option to sort hotels on the basis of the personalized recommendations ( ...
doi:10.1007/978-3-642-40477-1_21
fatcat:n75vmcnirvck7bxuclyac3p4wy
Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content
2012
Marketing science (Providence, R.I.)
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Based on the estimates from the model, we infer the economic impact of various location and service characteristics of hotels. ...
Our user studies, using ranking comparisons from several thousand users, validate the superiority of our ranking system relative to existing systems on several travel search engines. ...
The authors thank Susan Athey, Peter Fader, Francois Moreau, Aviv Nevo, Minjae Song, Daniel Spulber, Catherine Tucker, and Hal Varian ...
doi:10.1287/mksc.1110.0700
fatcat:j2blvj54zbhyfdvmlg57nv5kke
Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowd-Sourced Content
2011
Social Science Research Network
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Based on the estimates from the model, we infer the economic impact of various location and service characteristics of hotels. ...
Our user studies, using ranking comparisons from several thousand users, validate the superiority of our ranking system relative to existing systems on several travel search engines. ...
The authors thank Susan Athey, Peter Fader, Francois Moreau, Aviv Nevo, Minjae Song, Daniel Spulber, Catherine Tucker, and Hal Varian ...
doi:10.2139/ssrn.1856558
fatcat:wqauox64snabhbjx3lk6llyl3q
Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue
2014
Management science
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On the other hand, hotels with a lower customer rating are more likely to benefit from being placed on the top of the screen. ...
I n this paper, we study the effects of three different kinds of search engine rankings on consumer behavior and search engine revenues: direct ranking effect, interaction effect between ranking and product ...
These papers focused primarily on evaluating the effect of screen position on user behavior, controlling for the quality of the advertisement. ...
doi:10.1287/mnsc.2013.1828
fatcat:i2iem6kiqbgrnfd6arvvsqx4hy
Review Recommendation for Points of Interest's Owners
2017
Proceedings of the 28th ACM Conference on Hypertext and Social Media - HT '17
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for before determining whether a review is helpful) analysis for predicting the helpfulness of online customer reviews. ...
Zhou and Guo [2017] examine social influence effects on review helpfulness through effect of review order, finding that the order of a review negatively relates to review helpfulness. ...
doi:10.1145/3078714.3078744
dblp:conf/ht/PradoM17
fatcat:awtodkdribhrnelfkobv56r4iu
The electronic word of mouth as a context variable in the hotel management decision-making process
2019
Cuadernos de Gestión
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The tourism literature claims more research regarding the electronic word-of-mouth (eWOM) impacts management, as well as the application of multidisciplinary theories, specifically in hotels. ...
In order to fill this gap, and taking advantage of the Behavioural Reasoned Theory (BRT), this research proposes and validates a model of the decision-making process of hotel managers about accepting and ...
Kim et al (2015) investigate the impact of the choice of approach to online review management on hotel performance. ...
doi:10.5295/cdg.170860cb
fatcat:novjaazz3rhsvmpoqydu4cvui4
Social Recommendation Model with User Trust and Item Ratings Using Collaborative Filtering Technique in Hotel Application
2020
Informatica : Journal of Applied Machines Electrical Electronics Computer Science and Communication Systems
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It focuses on the rating prediction role in the current framework and has shown that integrating user social confidence data will boost the output of recommendations. ...
If the information is accessible on the server, all the adjacent devices are enabled and a peer to peer mode of communication is initiated. User reviews from a graphical forum are shown. ...
To filter the list of hotels, the extraction process is performed to filter the list of friendly hotels and reveal them to the user. Finally, the standard of the hotel consumer recommends. ...
doi:10.47812/ijamecs2010103
fatcat:aj57sw5wwvca3gxl2wa7wxhck4
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