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A Case Base Travel Advisory System for Personalization

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dc.contributor.author Thin, Ei Ei
dc.contributor.author Mar, Win
dc.date.accessioned 2019-07-29T07:01:02Z
dc.date.available 2019-07-29T07:01:02Z
dc.date.issued 2009-12-30
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1450
dc.description.abstract Web personalization and one to one marketing have been introduced as strategy and marketing tools. By using historical and present information of customers, organization can learn, predicts customer’s behavior and develop services to fit potential customers. There are two learning approaches using in this study. First, Personalization Learner by Group Properties is learning from all users in one group to find the group interests of travel information by using given data on user ages and genders. Second, Personalization Learner by User Behavior: user profile, user behaviors and trip features will be analyzed to find the unique interest of each web user. The results from this study reveal that it is possible to develop Personalization in a Travel Advisory System (PTAS). In this study, a Personalization in Travel Advisory System (PTAS) is introduced to manage traveling information for users. It provides the information that matches the users’ interests. This system applies the Reinforcement learning to analyze, learn customer behaviors and recommended conditions to meet customer interests. en_US
dc.language.iso en en_US
dc.publisher Fourth Local Conference on Parallel and Soft Computing en_US
dc.title A Case Base Travel Advisory System for Personalization en_US
dc.type Article en_US

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