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New Technology of Library and Information Service  2014, Vol. 30 Issue (4): 27-33    DOI: 10.11925/infotech.1003-3513.2014.04.05
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Research on Information Fusion for Multiple-sensor Expert Features
Li Gang, Ye Guanghui
Center for the Studies of Information Resources, Wuhan University, Wuhan 430072, China
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[Objective] In order to fully get expert resources, the authors have carried out the information fusion research based on multiple-sensor expert features. [Methods] Firstly, in the view of working process of sensor, this paper brings out three methods based on knowledge sensor, Web sensor and social network sensor in sequence. Secondly, focusing on resource balancing degree, it designs the method of expert feature recognition based on multiple-sensor information to solve the conflict which three obtained eigenvectors give rise to. [Results] Matching the expert feature from C-DBLP, the degree of similarity is close to thirty-nine percent, which can be accepted among similar methods. [Limitations] On one hand, many experts identified are from universities and institutes, correspondingly, academic resources for feature recognition are of great account. On the other hand, the site collection for Web sensor can be extended further. [Conclusions] Under the circumstance of controlled relationship between keywords, this method can be applied to many aspects, such as the construction of expert teams, the recommendation and retrieval of experts, and so on.

Key wordsFeature recognition      Sensor      Social network      Resource balancing degree     
Received: 17 December 2013      Published: 19 May 2014
:  G353  

Cite this article:

Li Gang, Ye Guanghui. Research on Information Fusion for Multiple-sensor Expert Features. New Technology of Library and Information Service, 2014, 30(4): 27-33.

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