论高校图书馆情景敏感服务的实现方式
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摘要
情景敏感服务是高校图书馆服务变革的方向。文章主要探讨情景敏感服务的4种主要的实现方式。情景敏感的信息检索服务在掌握用户的真正需求方面具有独特的优势,能更好地解决传统信息检索不能解决的"模糊性"和"不确定性"等问题,提高检索性能;情景敏感的个性化定制服务则在充分考虑用户的时间、位置、工作活动等情景信息的基础上实现定制服务的动态化推送;情景敏感信息推荐服务基于用户—资源—情景之间的多维匹配关系,在推荐实时性、个性化、有效性方面体现出天然的优势;情景敏感的学科咨询服务综合考虑用户、咨询问题、咨询馆员等各种情景因素,从而为用户提供量身定制的咨询答案,深化了学科咨询的内涵。
Context-aware service is the transformation direction of academic library service.There are four realization ways.Context-aware information retrieval service owns unique advantages in getting user's real needs and can resolve the traditional problems of ambiguity and uncertainty and improve retrieval performance.Context-aware customized service can realize dynamic recommendation by using user's context,such as time,location and activity.Context-aware recommendation service embodies natural advantages in real-time,personalization and effectiveness based on muti-dimensional matching relation of user-resource-context.Context-aware subject reference service can provide customized reference answer by considering user,reference question and librarian context,and deepen the connotation of subject reference service.
Context-aware service is the transformation direction of academic library service.There are four realization ways.Context-aware information retrieval service owns unique advantages in getting user's real needs and can resolve the traditional problems of ambiguity and uncertainty and improve retrieval performance.Context-aware customized service can realize dynamic recommendation by using user's context,such as time,location and activity.Context-aware recommendation service embodies natural advantages in real-time,personalization and effectiveness based on muti-dimensional matching relation of user-resource-context.Context-aware subject reference service can provide customized reference answer by considering user,reference question and librarian context,and deepen the connotation of subject reference service.
引文
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[17]Park H S,Yoo J O,Cho S B.A Context-Aware Music Recommendation System Using Fuzzy Bayesian Networks with Utility Theory[C].Proceedings of the FSKD.Berlin:Springer-Verlag,2006:970-979.
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[19]祝锡永,潘旭伟,王正成.基于情境的知识共享与重用方法研究[J].情报学报,2007(2):179-184.
[20]周宁丽,张智雄,初景利.用户需求嵌接、流程驱动、情景敏感型9-9网络参考咨询服务[J].图书情报工作,2007(10):100-103.
[2]Broder A.The Next Generation Web Search and the Demise of the Classic IR Model[C/OL].ECIR 2007.[2018-02-13].http://www.doc88.com/p-7028949519504.html.
[3]周新.情境感知的物联网信息检索技术研究[D].大连:大连海事大学,2011.
[4]Lee H,Kwon J.Improving Context Awareness Information Retrieval with Online Cocial Networks[C].First ACIS/JNU International Conference on Computers,Networks,Systems,and Industrial Engineering,2011:391-395.
[5]Ingwersen P.Cognitive Perspectives of Information Retrieval Interaction:Elements of a Cognitive IR Theory[J].Journal of Documentation,1996,52(1):3-50.
[6]洪颖.基于情境感知的信息检索研究综述[J].图书情报工作,2014(16):143-148.
[7]王建涛,胡明玲.工具条在图书馆信息服务中的应用[J].图书情报工作,2007(2):121-124,134.
[8]周虹.基于Google工具栏定制图书馆个性化工具栏[J].现代图书情报技术,2009(6):66-69.
[9]吉聪.图书馆Widget:面对个性化定制时代[J].图书馆论坛,2009(2):47-48.
[10]Dao T H,Jeong S R,Ahn H.A Novel Recommendation Model of Location-Based Advertising:Context-Aware Collaborative Filtering Using GA Approach[J].Expert Systems with Applications,2012,39(3):3731-3739.
[11]Pessemmier T D,Dooms S,Martens L.Context-Aware Recommendations Through Context and Activity Recognition in a Mobile Environment[J].Multimedia Tools and Applications,2013,72(3):2925-2948.
[12]EI Helou S,Salzmann C,Gillet D.The 3APersonalized,Contextual and Relation-Based Recommender System[J].Journal of Universal Computer Science,2010,16(16):2179-2195.
[13]Hosseini-Pozveh M,Nematbakhsh M.A Multidimensional Approach for Context-Aware Recommendation in Mobile Commerce[J].International Journal of Computer Science and Information Security,2009,3(1):86-91.
[14]Chen A.Context-aware Collaborative Filtering System:Predicting Users Preferences in Ubiquitous Computing Environment[C].Proceedings of the LoCA,2005:244-253.
[15]Baltrunas L,Ricci F.Context-Dependent Items Generation in Collaborative Filtering[C/OL].Proceedings of the Workshop on Context-aware Recommender Systems,2009.[2018-02-17].http://www.docin.com/p-1080299086.html.
[16]Yap G E,Tan A H,Pang H H.Discovering and Exploiting Causal Dependencies for Robust Mobile Context-Aware Recommenders[J].IEEE Transactions on Knowledge and Data Engineering,2007,19(7):977-992.
[17]Park H S,Yoo J O,Cho S B.A Context-Aware Music Recommendation System Using Fuzzy Bayesian Networks with Utility Theory[C].Proceedings of the FSKD.Berlin:Springer-Verlag,2006:970-979.
[18]Yu Z W,Zhou X S,Zhang D Q,et al.Supporting Context-Aware Media Recommendations for Smart Phones[J].IEEE Pervasive Computing,2006,5(3):68-75.
[19]祝锡永,潘旭伟,王正成.基于情境的知识共享与重用方法研究[J].情报学报,2007(2):179-184.
[20]周宁丽,张智雄,初景利.用户需求嵌接、流程驱动、情景敏感型9-9网络参考咨询服务[J].图书情报工作,2007(10):100-103.