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

  • Yi Zeng
  • Tielin Zhang
  • Hongwei Hao
Conference paper

DOI: 10.1007/978-3-319-09912-5_22

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8610)
Cite this paper as:
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

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.

Keywords

Semantic Relatedness Active Recommendation User Interests Knowledge Base Information Integration 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Yi Zeng
    • 1
  • Tielin Zhang
    • 1
  • Hongwei Hao
    • 1
  1. 1.Institute of AutomationChinese Academy of SciencesBeijingChina

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