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  • × year_i:[2010 TO 2020}
  • × author_ss:"Liu, Y."
  1. Liu, Y.; Xu, S.; Blanchard, E.: ¬A local context-aware LDA model for topic modeling in a document network (2017) 0.01 
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    Abstract
    With the rapid development of the Internet and its applications, growing volumes of documents increasingly become interconnected to form large-scale document networks. Accordingly, topic modeling in a network of documents has been attracting continuous research attention. Most of the existing network-based topic models assume that topics in a document are influenced by its directly linked neighbouring documents in a document network and overlook the potential influence from indirectly linked ones. The existing work also has not carefully modeled variations of such influence among neighboring documents. Recognizing these modeling limitations, this paper introduces a novel Local Context-Aware LDA Model (LC-LDA), which is capable of observing a local context comprising a rich collection of documents that may directly or indirectly influence the topic distributions of a target document. The proposed model can also differentiate the respective influence of each document in the local context on the target document according to both structural and temporal relationships between the two documents. The proposed model is extensively evaluated through multiple document clustering and classification tasks conducted over several large-scale document sets. Evaluation results clearly and consistently demonstrate the effectiveness and superiority of the new model with respect to several state-of-the-art peer models.
  2. Liu, Y.; Rafols, I.; Rousseau, R.: ¬A framework for knowledge integration and diffusion (2012) 0.01 
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    Abstract
    Purpose - This paper aims to introduce a general framework for the analysis of knowledge integration and diffusion using bibliometric data. Design/methodology/approach - The authors propose that in order to characterise knowledge integration and diffusion of a given issue (the source, for example articles on a topic or by an organisation, etc.), one has to choose a set of elements from the source (the intermediary set, for example references, keywords, etc.). This set can then be classified into categories (cats), thus making it possible to investigate its diversity. The set can also be characterised according to the coherence of a network associated to it. Findings - This framework allows a methodology to be developed to assess knowledge integration and diffusion. Such methodologies can be useful for a number of science policy issues, including the assessment of interdisciplinarity in research and dynamics of research networks. Originality/value - The main contribution of this article is to provide a simple and easy to use generalisation of an existing approach to study interdisciplinarity, bringing knowledge integration and knowledge diffusion together in one framework.
  3. Liu, Y.; Rousseau, R.: Citation analysis and the development of science : a case study using articles by some Nobel prize winners (2014) 0.01 
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    Date
    29. 1.2014 16:31:35
  4. Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019) 0.00 
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    Date
    20. 1.2015 18:30:22

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