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  • × author_ss:"Chen, X."
  1. Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013) 0.02
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    Abstract
    The number of research studies on social tagging has increased rapidly in the past years, but few of them highlight the characteristics and research trends in social tagging. A set of 862 academic documents relating to social tagging and published from 2005 to 2011 was thus examined using bibliometric analysis as well as the social network analysis technique. The results show that social tagging, as a research area, develops rapidly and attracts an increasing number of new entrants. There are no key authors, publication sources, or research groups that dominate the research domain of social tagging. Research on social tagging appears to focus mainly on the following three aspects: (a) components and functions of social tagging (e.g., tags, tagging objects, and tagging network), (b) taggers' behaviors and interface design, and (c) tags' organization and usage in social tagging. The trend suggest that more researchers turn to the latter two integrated with human computer interface and information retrieval, although the first aspect is the fundamental one in social tagging. Also, more studies relating to social tagging pay attention to multimedia tagging objects and not only text tagging. Previous research on social tagging was limited to a few subject domains such as information science and computer science. As an interdisciplinary research area, social tagging is anticipated to attract more researchers from different disciplines. More practical applications, especially in high-tech companies, is an encouraging research trend in social tagging.
  2. Wu, Y.-f.B.; Li, Q.; Bot, R.S.; Chen, X.: Finding nuggets in documents : a machine learning approach (2006) 0.01
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    Abstract
    Document keyphrases provide a concise summary of a document's content, offering semantic metadata summarizing a document. They can be used in many applications related to knowledge management and text mining, such as automatic text summarization, development of search engines, document clustering, document classification, thesaurus construction, and browsing interfaces. Because only a small portion of documents have keyphrases assigned by authors, and it is time-consuming and costly to manually assign keyphrases to documents, it is necessary to develop an algorithm to automatically generate keyphrases for documents. This paper describes a Keyphrase Identification Program (KIP), which extracts document keyphrases by using prior positive samples of human identified phrases to assign weights to the candidate keyphrases. The logic of our algorithm is: The more keywords a candidate keyphrase contains and the more significant these keywords are, the more likely this candidate phrase is a keyphrase. KIP's learning function can enrich the glossary database by automatically adding new identified keyphrases to the database. KIP's personalization feature will let the user build a glossary database specifically suitable for the area of his/her interest. The evaluation results show that KIP's performance is better than the systems we compared to and that the learning function is effective.
    Date
    22. 7.2006 17:25:48
  3. Chen, X.: ¬The influence of existing consistency measures on the relationship between indexing consistency and exhaustivity (2008) 0.01
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    Content
    Consistency studies have discussed the relationship between indexing consistency and exhaustivity, and it commonly accepted that higher exhaustivity results in lower indexing consistency. However, this issue has been oversimplified, and previous studies contain significant misinterpretations. The aim of this study is investigate the relationship between consistency and exhaustivity based on a large sample and to analyse the misinterpretations in earlier studies. A sample of 3,307 monographs, i.e. 6,614 records was drawn from two Chinese bibliographic catalogues. Indexing consistency was measured using two formulae which were popular in previous indexing consistency studies. A relatively high level of consistency was found (64.21% according to the first formula, 70.71% according to the second). Regarding the relationship between consistency and exhaustivity, it was found that when two indexers had identical exhaustivity, indexing consistency was substantially high. On the contrary, when they had different levels of exhaustivity, consistency was significantly low. It was inevitable with the use of the two formulae. Moreover, a detailed discussion was conducted to analyse the misinterpretations in previous studies.
  4. Chen, X.: Fair use of electronic sources in libraries (1996) 0.01
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