Number of co-authors:10
Number of publications with 3 favourite co-authors:Rong Zheng:Zan Huang:Kaiquan Xu:
Jiexun Li's 3 most productive colleagues in number of publications:Hsinchun Chen:145Xin Li:23Wingyan Chung:20
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Publications by Jiexun Li (bibliography)
Xu, Kaiquan, Li, Jiexun and Liao, Stephen Shaoyi (2011): Sentiment community detection in social networks. In: Proceedings of the 2011 iConference 2011. pp. 804-805. Available online
With the increasing popularity of social networking sites and Web 2.0, people are building social relationships and expressing their opinions in the cyberspace. In this study, we introduce several novel methods to identify online communities with similar sentiments in online social networks. Our preliminary experiment on a real-world dataset demonstrates that our proposed method can detect interesting sentiment communities in social networks.
© All rights reserved Xu et al. and/or ACM Press
Li, Jiexun, Zhang, Zhu, Li, Xin and Chen, Hsinchun (2008): Kernel-based learning for biomedical relation extraction. In JASIST - Journal of the American Society for Information Science and Technology, 59 (5) pp. 756-769. Available online
Li, Xin, Chen, Hsinchun, Zhang, Zhu and Li, Jiexun (2007): Automatic patent classification using citation network information: an experimental study in nanotechnology. In: JCDL07: Proceedings of the 7th ACM/IEEE-CS Joint Conference on Digital Libraries 2007. pp. 419-427. Available online
Classifying and organizing documents in repositories is an active research topic in digital library studies. Manually classifying the large volume of patents and patent applications managed by patent offices is a labor-intensive task. Many previous studies have employed patent contents for patent classification with the aim of automating this process. In this research we propose to use patent citation information, especially the citation network structure information, to address the patent classification problem. We adopt a kernel-based approach and design kernel functions to capture content information and various citation-related information in patents. These kernels. performances are evaluated on a testbed of patents related to nanotechnology. Evaluation results show that our proposed labeled citation graph kernel, which utilized citation network structures, significantly outperforms the kernels that use no citation information or only direct citation information.
© All rights reserved Li et al. and/or ACM Press
Leroy, Gondy, Li, Jiexun, Chung, Wingyan and Eggers, Shauna (2006): End User Evaluation of Query Formulation and Results Review Tools in Three Medical Meta-Search Engines. In International Journal of Medical Informatics, 11 pp. 780-789.
Zheng, Rong, Li, Jiexun, Chen, Hsinchun and Huang, Zan (2006): A framework for authorship identification of online messages: Writing-style features and classification techniques. In JASIST - Journal of the American Society for Information Science and Technology, 57 (3) pp. 378-393. Available online
Li, Jiexun, Zheng, Rong and Chen, Hsinchun (2006): From fingerprint to writeprint. In Communications of the ACM, 49 (4) pp. 76-82. Available online
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