Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/72460
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dc.contributor.authorDIe Huen_US
dc.contributor.authorDanaitun Pongpatcharatrontepen_US
dc.contributor.authorSirikorn Santirojanakulen_US
dc.contributor.authorAchara Khamaksornen_US
dc.date.accessioned2022-05-27T08:25:53Z-
dc.date.available2022-05-27T08:25:53Z-
dc.date.issued2022-01-01en_US
dc.identifier.other2-s2.0-85127600461en_US
dc.identifier.other10.1109/ECTIDAMTNCON53731.2022.9720413en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85127600461&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/72460-
dc.description.abstractWith the tremendous development of the Internet, e-commerce and social networks, research on Social Recommendation Systems has become a hot topic to solve information overload and respond to diverse individual demands. However, many of the existing social recommendation methods lack an in-depth analysis of long-stay users from cross-cultural backgrounds, which causes insufficient social recommendations, since the social attributes and requirements of these users differ from those of short-stay tourists, local organisations or residents. Therefore, taking Chinese long-stayers in Chiang Mai as a case study, this paper follows the Knowledge Management process with the aim of producing a social recommendation framework based on social networks to provide Chinese long-stayers with filtered and efficient social recommendations. The research employs qualitative and quantitative methods to investigate the research problems and conducts online surveys and in-depth interviews to collect the individual and collective data and analyse them using Social Network Analysis. The proposed social recommendation framework aims to benefit Chinese long-stayers and any other organisations that need social recommendations or innovative business and management strategies in relation to Chinese long-stayers in Chiang Mai. The preliminary work will contribute to the current accumulative knowledge of the impact of social networks of Chinese long-stayers on social recommendation performance in a cross-cultural context.en_US
dc.subjectArts and Humanitiesen_US
dc.subjectComputer Scienceen_US
dc.subjectDecision Sciencesen_US
dc.subjectEngineeringen_US
dc.titleA Social Recommendation Framework for Chinese Long-stayers in Chiang Maien_US
dc.typeConference Proceedingen_US
article.title.sourcetitle7th International Conference on Digital Arts, Media and Technology, DAMT 2022 and 5th ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications Engineering, NCON 2022en_US
article.stream.affiliationsChiang Mai Universityen_US
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