Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (19): 224-226.DOI: 10.3778/j.issn.1002-8331.2010.19.065

• 工程与应用 • Previous Articles     Next Articles

Personalized recommendation algorithm for smart museum environment

ZHOU Shan-dan,ZHOU Xing-she,WANG Hai-peng,NI Hong-bo,ZHANG Gui-ying,MIAO Qiang   

  1. College of Computer Science,Northwestern Polytechnical University,Xi’an 710072,China
  • Received:2009-03-18 Revised:2009-05-11 Online:2010-07-01 Published:2010-07-01
  • Contact: ZHOU Shan-dan

智能博物馆环境下的个性化推荐算法

周珊丹,周兴社,王海鹏,倪红波,张桂英,苗强   

  1. 西北工业大学计算机学院,西安710072
  • 通讯作者: 周珊丹

Abstract: The rapid development of Internet and multimedia technology plays a catalytic role in the emerging requirement
for diversiform and personalized information service.The next-generation museum is to become a place that is not merely
for the collection,protection and study of historical relics.It must also cater for the personalized preferences of different visitors
in order to fully unleash its vital power in the exhibition and spread of culture.Currently available various service personalization
technologies bring hope and challenge to the construction of intelligent museum system.Increasing amount and
variety of information provides visitors with more choices,but on the other hand also heavens the burden for people to locate
the information that is really interesting.A personalized,intelligent recommendation framework and related algorithms are
proposed for smart museum applications.Within this framework,the personal visit preference of an individual is learned by
collecting and analyzing his or her history visit information.Personalized visit recommendation is adapted and provided to visitors
by considering their different backgrounds,visit preferences and the history public evaluation of the exhibits.

摘要: 随着通信和微电子技术的高速发展,用户对信息的需求呈现出个性化、多样化及复杂化的特点。新一代的博物馆系统,更加追求对文物的展现及和文化的传播功能,迫切需要适应当今用户对信息的个性化需求的特点。当前众多的个性化服务技术为智能博物馆的研究带来机遇和挑战,如何使个性化技术应用到实际的博物馆中是有待研究的问题。以下一代博物馆为背景,提出了一种在该环境下的个性化推荐算法。该算法综合考虑用户个人喜好及文物历史大众评价信息,为用户推荐合适文物,从而提高用户在博物馆中的游览体验。

CLC Number: