Publication statistics

Pub. period:2011-2012
Pub. count:4
Number of co-authors:9



Co-authors

Number of publications with 3 favourite co-authors:

Daqing He:3
Wei Lu:1
Zhen Yue:1

 

 

Productive colleagues

Jiepu Jiang's 3 most productive colleagues in number of publications:

Daqing He:17
Dan Wu:6
Wei Lu:5
 
 
 

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Jiepu Jiang

 

Publications by Jiepu Jiang (bibliography)

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2012
 
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Jiang, Jiepu, Yue, Zhen, Han, Shuguang and He, Daqing (2012): Finding readings for scientists from social websites. In: Proceedings of the 35th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2012. pp. 1075-1076. Available online

Current search systems are designed to find relevant articles, especially topically relevant ones, but the notion of relevance largely depends on search tasks. We study the specific task that scientists are searching for worth-reading articles beneficial for their research. Our study finds: users' perception of relevance and preference of reading are only moderately correlated; current systems can effectively find readings that are highly relevant to the topic, but 36% of the worth-reading articles are only marginally relevant or even non-relevant. Our system can effectively find those worth-reading but marginally relevant or non-relevant articles by taking advantages of scientists' recommendations in social websites.

© All rights reserved Jiang et al. and/or ACM Press

2011
 
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Jiang, Jiepu, He, Daqing and Ni, Chaoqun (2011): Social reference: aggregating online usage of scientific literature in CiteULike for clustering academic resources. In: JCDL11 Proceedings of the 2010 Joint International Conference on Digital Libraries 2011. pp. 401-402. Available online

Citation-based methods have been widely studied and employed for clustering academic resources and mapping science. Although effective, these methods suffer from citation delay. In this study, we extend reference and citation analysis to a broader notion from social perspective. We coin the term "social reference" to refer to the references of literatures in social academic web environment. We propose clustering methods using social reference information from CiteULike. We experiment for journal clustering and author clustering using social reference and compare with citation-based methods. Our experiments indicate: first, social reference implies connections among literatures which are as effective as citation in clustering academic resources; second, in practical settings, social reference-based clustering methods are not as effective as citation-based ones due to the sparseness of social reference data, but they can outperform in clustering new resources that have few citation.

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Wu, Dan, He, Daqing, Jiang, Jiepu, Dong, Wuyi and Vo, Kim Thien (2011): Academic research in iSchools: state and implications. In: Proceedings of the 2011 iConference 2011. pp. 203-210. Available online

As the information field rapidly evolves, so do the academic research programs in Information Schools (iSchools). In this paper, we examine the current academic research state of iSchools through quantitative study of publically-available online data related to the educational background, research interests, publications, research funding, and collaborations. Some important findings in our study include that iSchools are appropriate institutions for integrating researchers from diverse disciplines; the intersection of information, technology, and users has been established as the core research focus of iSchools; iSchools are developing ways to understand, integrate, and model the interaction among related disciplines; iSchools are attracting external support from a diverse group of funding agencies; and iSchools have forged strong connections and collaborations in order to build one discipline.

© All rights reserved Wu et al. and/or ACM Press

 
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Wu, Xuefeng, Lu, Wei and Jiang, Jiepu (2011): Journal evaluation using the importance of authors in co-authorship network. In: Proceedings of the 2011 iConference 2011. pp. 800-801. Available online

In this poster, we propose to evaluate journal influence based on journal authors' importance in co-authorship network. Preliminary results of evaluating Chinese LIS journals are presented.

© All rights reserved Wu et al. and/or ACM Press

 
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