Search (13 results, page 1 of 1)

  • × author_ss:"Liu, X."
  • × language_ss:"e"
  • × year_i:[2010 TO 2020}
  1. Liu, X.; Zheng, W.; Fang, H.: ¬An exploration of ranking models and feedback method for related entity finding (2013) 0.01 
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    Source
    Information processing and management. 49(2013) no.5, S.995-1007
  2. Liu, X.; Yu, S.; Janssens, F.; Glänzel, W.; Moreau, Y.; Moor, B.de: Weighted hybrid clustering by combining text mining and bibliometrics on a large-scale journal database (2010) 0.00 
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    Abstract
    We propose a new hybrid clustering framework to incorporate text mining with bibliometrics in journal set analysis. The framework integrates two different approaches: clustering ensemble and kernel-fusion clustering. To improve the flexibility and the efficiency of processing large-scale data, we propose an information-based weighting scheme to leverage the effect of multiple data sources in hybrid clustering. Three different algorithms are extended by the proposed weighting scheme and they are employed on a large journal set retrieved from the Web of Science (WoS) database. The clustering performance of the proposed algorithms is systematically evaluated using multiple evaluation methods, and they were cross-compared with alternative methods. Experimental results demonstrate that the proposed weighted hybrid clustering strategy is superior to other methods in clustering performance and efficiency. The proposed approach also provides a more refined structural mapping of journal sets, which is useful for monitoring and detecting new trends in different scientific fields.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.6, S.1105-1119
  3. Liu, X.; Kaza, S.; Zhang, P.; Chen, H.: Determining inventor status and its effect on knowledge diffusion : a study on nanotechnology literature from China, Russia, and India (2011) 0.00 
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    Abstract
    In an increasingly global research landscape, it is important to identify the most prolific researchers in various institutions and their influence on the diffusion of knowledge. Knowledge diffusion within institutions is influenced by not just the status of individual researchers but also the collaborative culture that determines status. There are various methods to measure individual status, but few studies have compared them or explored the possible effects of different cultures on the status measures. In this article, we examine knowledge diffusion within science and technology-oriented research organizations. Using social network analysis metrics to measure individual status in large-scale coauthorship networks, we studied an individual's impact on the recombination of knowledge to produce innovation in nanotechnology. Data from the most productive and high-impact institutions in China (Chinese Academy of Sciences), Russia (Russian Academy of Sciences), and India (Indian Institutes of Technology) were used. We found that boundary-spanning individuals influenced knowledge diffusion in all countries. However, our results also indicate that cultural and institutional differences may influence knowledge diffusion.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.6, S.1166-1176
  4. Liu, X.: Generating metadata for cyberlearning resources through information retrieval and meta-search (2013) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.4, S.771-786
  5. Liu, X.; Jia, H.: Answering academic questions for education by recommending cyberlearning resources (2013) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.8, S.1707-1722
  6. Liu, X.; Turtle, H.: Real-time user interest modeling for real-time ranking (2013) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.8, S.1557-1576
  7. Liu, X.; Guo, C.; Zhang, L.: Scholar metadata and knowledge generation with human and artificial intelligence (2014) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.6, S.1187-1201
  8. Zhang, X.; Fang, Y.; He, W.; Zhang, Y.; Liu, X.: Epistemic motivation, task reflexivity, and knowledge contribution behavior on team wikis : a cross-level moderation model (2019) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.5, S.448-461
  9. Zhang, C.; Liu, X.; Xu, Y.(C.); Wang, Y.: Quality-structure index : a new metric to measure scientific journal influence (2011) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.4, S.643-653
  10. Liu, X.; Zhang, J.; Guo, C.: Full-text citation analysis : a new method to enhance scholarly networks (2013) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.9, S.1852-1863
  11. Liu, X.; Qin, J.: ¬An interactive metadata model for structural, descriptive, and referential representation of scholarly output (2014) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.5, S.964-983
  12. Chen, Z.; Huang, Y.; Tian, J.; Liu, X.; Fu, K.; Huang, T.: Joint model for subsentence-level sentiment analysis with Markov logic (2015) 0.00 
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    Journal of the Association for Information Science and Technology. 66(2015) no.9, S.1913-1922
  13. Jiang, Z.; Liu, X.; Chen, Y.: Recovering uncaptured citations in a scholarly network : a two-step citation analysis to estimate publication importance (2016) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.7, S.1722-1735

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