Tang, J; Zhang, J; Jin, RM; Yang, Z; Cai, KK; Zhang, L; Su, Z. 2011. Topic level expertise search over heterogeneous networks. MACHINE LEARNING 82 (2): 211-237

[Eugene Garfield]

Tang, J; Zhang, J; Jin, RM; Yang, Z; Cai, KK; Zhang, L; Su, Z. 2011. Topic 
level expertise search over heterogeneous networks. MACHINE LEARNING 82 
(2): 211-237, Sp. Iss. SI.presented at International Conference on Machine 
Learning/ Workshop on Machine Learning and Graphs in Helsinki, FINLAND, 2008.

Author Full Name(s): Tang, Jie; Zhang, Jing; Jin, Ruoming; Yang, Zi; Cai, Keke; 
Zhang, Li; Su, Zhong
Language: English
Document Type: Proceedings Paper

Author Keywords: Social network; Information extraction; Name 
disambiguation; Topic modeling; Expertise search; Association search

Abstract: In this paper, we present a topic level expertise search framework for 
heterogeneous networks. Different from the traditional Web search engines 
that perform retrieval and ranking at document level (or at object level), we 
investigate the problem of expertise search at topic level over heterogeneous 
networks. In particular, we study this problem in an academic search and 
mining system, which extracts and integrates the academic data from the 
distributed Web. We present a unified topic model to simultaneously model 
topical aspects of different objects in the academic network. Based on the 
learned topic models, we investigate the expertise search problem from three 
dimensions: ranking, citation tracing analysis, and topical graph search. 
Specifically, we propose a topic level random walk method for ranking the 
different objects. In citation tracing analysis, we aim to uncover how a piece of 
work influences its follow-up work. Finally, we have developed a topical graph 
search function, based on the topic modeling and citation tracing analysis. 
Experimental results show that various expertise search and mining tasks can 
indeed benefit from the proposed topic level analysis approach.

Addresses: [Tang, Jie; Zhang, Jing; Yang, Zi] Tsinghua Univ, Dept Comp Sci & 
Technol, Beijing 100084, Peoples R China; [Jin, Ruoming] Kent State Univ, Dept 
Comp Sci, Kent, OH 44241 USA; [Cai, Keke; Zhang, Li; Su, Zhong] IBM Corp, 
China Res Lab, Beijing, Peoples R China
Reprint Address: Tang, J, Tsinghua Univ, Dept Comp Sci & Technol, Beijing 
100084, Peoples R China.

E-mail Address: jietang at tsinghua.edu.cn; zhangjing at keg.cs.tsinghua.edu.cn; 
jin at cs.kent.edu; yz at keg.cs.tsinghua.edu.cn; caikeke at cn.ibm.com; 
lizhang at cn.ibm.com; suzhong at cn.ibm.com
ISSN: 0885-6125
DOI: 10.1007/s10994-010-5212-9
PDF: http://keg.cs.tsinghua.edu.cn/persons/tj/publications/MLJ11-Tang-et-al-
topic-level-search-in-heterogeneous-networks.pdf