The similar scholar recommendation in Schol@t

Lots of scholars depend on the Internet for rapid access to the other scholar's research information and build cooperative relationship. But current systems for finding another scholar who share the same research field or interests do not adequately satisfy the need of scholars; moreover the process of seeking is time-consuming and difficult. In this paper, we use the data from scholar's profile in Schol@t (the social network site we build for scholar) and provide a model base on the semantic analysis and social network analysis to recommend the right partner who has the same interest or in same research area to scholar.

[1]  Zenon Chaczko,et al.  Methods of Sensors Localization in Wireless Sensor Networks , 2007, 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (ECBS'07).

[2]  Jean-Claude König,et al.  MuR : A Distributed Preliminary Method For Location Techniques in Sensor Networks , 2006, 2006 IEEE International Conference on Wireless and Mobile Computing, Networking and Communications.

[3]  Paolo Santi,et al.  Investigating upper bounds on network lifetime extension for cell-based energy conservation techniques in stationary ad hoc networks , 2002, MobiCom '02.

[4]  T. Salthouse Expertise as the circumvention of human processing limitations. , 1991 .

[5]  Yong Tang,et al.  Semantic description of scholar-oriented social network cloud , 2010, The Journal of Supercomputing.

[6]  Wendi B. Heinzelman,et al.  Prolonging the lifetime of wireless sensor networks via unequal clustering , 2005, 19th IEEE International Parallel and Distributed Processing Symposium.

[7]  Liu Lu Expert Recommendation Based on Expert's Personal Knowledge Map , 2011 .

[8]  Maryam Fazel-Zarandi,et al.  Ontology-Based Expertise Finding , 2008, PAKM.

[9]  Wei Nuo Particle swarm optimization-based wireless sensor network nodes localization method , 2009 .

[10]  Deborah Estrin,et al.  Geography-informed energy conservation for Ad Hoc routing , 2001, MobiCom '01.

[11]  Yu-Chee Tseng,et al.  Fully power-aware and location-aware protocols for wireless multi-hop ad hoc networks , 2002, Proceedings. Eleventh International Conference on Computer Communications and Networks.

[12]  ChengXiang Zhai,et al.  Probabilistic Models for Expert Finding , 2007, ECIR.

[13]  M. de Rijke,et al.  Formal models for expert finding in enterprise corpora , 2006, SIGIR.

[14]  David W. McDonald,et al.  Recommending collaboration with social networks: a comparative evaluation , 2003, CHI '03.

[15]  Volker Wulf,et al.  Matching human actors based on their texts: design and evaluation of an instance of the ExpertFinding framework , 2005, GROUP.

[16]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[17]  Vikas Kawadia,et al.  Power control and clustering in ad hoc networks , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[18]  Raymond Y. K. Lau,et al.  A Personalized Researcher Recommendation Approach in Academic Contexts: Combining Social Networks and Semantic Concepts Analysis , 2010, PACIS.

[19]  Theodoros Lappas,et al.  Finding a team of experts in social networks , 2009, KDD.

[20]  Thomas R. Gruber,et al.  Toward principles for the design of ontologies used for knowledge sharing? , 1995, Int. J. Hum. Comput. Stud..

[21]  Robert S. Wachal,et al.  Webster's Dictionary of English Usage , 1993 .

[22]  Craig MacDonald,et al.  Voting for candidates: adapting data fusion techniques for an expert search task , 2006, CIKM '06.