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Active Recommendation of Tourist Attractions Based on Visitors Interests and Semantic Relatedness

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Active Media Technology (AMT 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8610))

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Abstract

Many visitors always search on tourist attractions related information on the Web so as to get more information on the places they are visiting or plan their next trips. In this study, we introduce CASIA-TAR, an active tourist attractions recommendation system, which provides relevant knowledge of specific tourist attractions and make recommendations for other relevant places to visit based on semantic relatedness among the specific tourist attraction and potentially interesting places. Two algorithms are introduced to calculate the semantic relatedness among different tourist attractions based on the tourist attraction semantic knowledge base with relevant knowledge mainly extracted from Web-based encyclopedias. As an integrated portal for tourist attraction recommendation, CASIA-TAR also provides images, news and microblog posts that are relevant to specific tourist attractions so that visitors could obtain relevant information in an integrated Web-based system.

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Zeng, Y., Zhang, T., Hao, H. (2014). Active Recommendation of Tourist Attractions Based on Visitors Interests and Semantic Relatedness. In: Ślȩzak, D., Schaefer, G., Vuong, S.T., Kim, YS. (eds) Active Media Technology. AMT 2014. Lecture Notes in Computer Science, vol 8610. Springer, Cham. https://doi.org/10.1007/978-3-319-09912-5_22

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  • DOI: https://doi.org/10.1007/978-3-319-09912-5_22

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09911-8

  • Online ISBN: 978-3-319-09912-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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