On exploiting content and citations together to compute similarity of scientific papers
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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The analysis of current approaches combining links and contents for scientific topics discovery reveals that the two sources of information (i.e. links and contents) are considered to be heterogeneous. Therefore, in this paper, we propose to integrate link and content information by exploiting the links semantics to enrich the textual content of documents. This idea is then implemented and evaluated. Experiments carried out on two real-world datasets show the good performances of our approach over state of the art techniques that combine citation and content information for scientific topics discovery.