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An exploratory study of the weather and calendar effects on tourism web site usage
Lim, Gyoo Gun,Kim, Do Hyun,Choi, Minnseok,Choi, Jin H.,Lee, Kun Chang Emerald Group Publishing Limited 2010 ONLINE INFORMATION REVIEW Vol.34 No.1
<B>Purpose</B> - The purpose of this paper is to investigate the weather and calendar effects on the usage pattern of a tourism web site. <B>Design/methodology/approach</B> - This paper analyses data from a yearlong web log involving 21,655,089 visitors to a popular tourism web site. The weather factors include rain, snow, cloud cover, and the calendar factors include seasons and holidays in order to test the proposed model. <B>Findings</B> - Using data from the Korea Tourism Organisation and the Korean Meteorological Administration, the results show that when it was rainy, cloudy, summer or a workday, the number of visitors to the tourism information web site was higher. <B>Originality/value</B> - The results provide managers involved in the tourism industry with useful insights for effective use of web sites by running them more efficiently and setting up appropriate marketing strategies in terms of the weather and calendar variables.
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An opinion-based decision model for recommender systems
Kim, Sea Woo,Chung, Chin-Wan,Kim, DaeEun Emerald Group Publishing Limited 2009 ONLINE INFORMATION REVIEW Vol.33 No.3
<B>Purpose</B> - A good recommender system helps users find items of interest on the web and can provide recommendations based on user preferences. In contrast to automatic technology-generated recommender systems, this paper aims to use dynamic expert groups that are automatically formed to recommend domain-specific documents for general users. In addition, it aims to test several effectiveness measures of rank order to determine if the top-ranked lists recommended by the experts were reliable. <B>Design/methodology/approach</B> - In the approach, expert groups evaluate web documents to provide a recommender system for general users. The authority and make-up of the expert group are adjusted through user feedback. The system also uses various measures to gauge the difference between the opinions of experts and those of general users to improve the evaluation effectiveness. <B>Findings</B> - The proposed system is efficient when there is major support from experts and general users. The recommender system is especially effective where there is a limited amount of evaluation data from general users. <B>Originality/value</B> - This is an original study of how to effectively recommend web documents to users based on the opinions of human experts. Simulation results were provided to show the effectiveness of the dynamic expert group for recommender systems.
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