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  • × author_ss:"Liu, X."
  1. Chen, S.Y.; Liu, X.: ¬The contribution of data mining to information science : making sense of it all (2005) 0.08
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    Theme
    Data Mining
  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) 0.05
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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.
    Theme
    Data Mining
  3. Clewley, N.; Chen, S.Y.; Liu, X.: Cognitive styles and search engine preferences : field dependence/independence vs holism/serialism (2010) 0.02
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    Abstract
    Purpose - Cognitive style has been identified to be significantly influential in deciding users' preferences of search engines. In particular, Witkin's field dependence/independence has been widely studied in the area of web searching. It has been suggested that this cognitive style has conceptual links with the holism/serialism. This study aims to investigate the differences between the field dependence/independence and holism/serialism. Design/methodology/approach - An empirical study was conducted with 120 students from a UK university. Riding's cognitive style analysis (CSA) and Ford's study preference questionnaire (SPQ) were used to identify the students' cognitive styles. A questionnaire was designed to identify users' preferences for the design of search engines. Data mining techniques were applied to analyse the data obtained from the empirical study. Findings - The results highlight three findings. First, a fundamental link is confirmed between the two cognitive styles. Second, the relationship between field dependent users and holists is suggested to be more prominent than that of field independent users and serialists. Third, the interface design preferences of field dependent and field independent users can be split more clearly than those of holists and serialists. Originality/value - The contributions of this study include a deeper understanding of the similarities and differences between field dependence/independence and holists/serialists as well as proposing a novel methodology for data analyses.
  4. Chen, M.; Liu, X.; Qin, J.: Semantic relation extraction from socially-generated tags : a methodology for metadata generation (2008) 0.01
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    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas