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  • × author_ss:"Li, C."
  1. Cheang, B.; Chu, S.K.W.; Li, C.; Lim, A.: ¬A multidimensional approach to evaluating management journals : refining pagerank via the differentiation of citation types and identifying the roles that management journals play (2014) 0.01 
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    Abstract
    In this article, the authors introduce two citation-based approaches to facilitate a multidimensional evaluation of 39 selected management journals. The first is a refined application of PageRank via the differentiation of citation types. The second is a form of mathematical manipulation to identify the roles that the selected management journals play. Their findings reveal that Academy of Management Journal, Academy of Management Review, and Administrative Science Quarterly are the top three management journals, respectively. They also discovered that these three journals play the role of a knowledge hub in the domain. Finally, when compared with Journal Citation Reports (Thomson Reuters, Philadelphia, PA), their results closely match expert opinions.
  2. Qu, B.; Cong, G.; Li, C.; Sun, A.; Chen, H.: ¬An evaluation of classification models for question topic categorization (2012) 0.00 
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    Abstract
    We study the problem of question topic classification using a very large real-world Community Question Answering (CQA) dataset from Yahoo! Answers. The dataset comprises 3.9 million questions and these questions are organized into more than 1,000 categories in a hierarchy. To the best knowledge, this is the first systematic evaluation of the performance of different classification methods on question topic classification as well as short texts. Specifically, we empirically evaluate the following in classifying questions into CQA categories: (a) the usefulness of n-gram features and bag-of-word features; (b) the performance of three standard classification algorithms (naive Bayes, maximum entropy, and support vector machines); (c) the performance of the state-of-the-art hierarchical classification algorithms; (d) the effect of training data size on performance; and (e) the effectiveness of the different components of CQA data, including subject, content, asker, and the best answer. The experimental results show what aspects are important for question topic classification in terms of both effectiveness and efficiency. We believe that the experimental findings from this study will be useful in real-world classification problems.

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