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Context-based Ontology-driven Recommendation Strategies for Tourism in Ubiquitous Computing

机译:普适计算中基于上下文的本体驱动的旅游推荐策略

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摘要

Tourism is an information-intensive business. At present, there are a lot of information and tourism resources available on the internet that lead to low searching efficiency and effectiveness, the user may get too many seeking results but not related to his interest, or few results than his expected. The user can know clearly what he wants, but sometime the user doesn't know what kind information he needs. User's demand can be formulated as direct demand and potential preference. At the same time, the study shows that there is strong relationship between the traveler's potential preference and the characteristics of tourism resources. In order to solve the information overload challenge, recommendation services are increasingly emerging. Currently, recommendation methods focus on dealing with personalized matching based on the user preference. However, these methods skip the user's direct demand. In this paper, we propose ontology-driven recommendation strategies based on user's context. The strategies use ontology to describe and integrate tourism resources, achieve the goal of associating user's direct needs and his potential preference as the context in recommendation. Moreover, theoretical analysis and experiments show that the proposed approach is feasible, the results of the evaluation are discussed.
机译:旅游业是一项信息密集型业务。当前,互联网上存在大量的信息和旅游资源,导致搜索效率和有效性低下,用户可能会获得太多的搜索结果,但与他的兴趣无关,或者结果很少。用户可以清楚地知道他想要什么,但是有时用户不知道他需要什么样的信息。用户需求可以表述为直接需求和潜在偏好。同时,研究表明,旅行者的潜在偏好与旅游资源的特征之间存在密切的关系。为了解决信息过载的挑战,推荐服务正在日益兴起。当前,推荐方法集中于基于用户偏好来处理个性化匹配。但是,这些方法会跳过用户的直接需求。在本文中,我们提出了基于用户上下文的本体驱动的推荐策略。该策略使用本体来描述和整合旅游资源,实现将用户的直接需求及其潜在偏好作为推荐上下文的目标。此外,理论分析和实验表明,该方法是可行的,并对评估结果进行了讨论。

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