Similarity computation for academic literature data is one of the interesting topics that have been discussed recently in information retrieval and data mining. Consequently, a variety of methods has been proposed to compute the similarity of scientific papers. In this paper, we present various similarity methods and evaluate their effectiveness via extensive experiments on a real-world dataset of scientific papers.
CITATION STYLE
Hamedani, M. R., & Kim, S. W. (2014). On computing similarity in academic literature data: Methods and evaluation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8597, pp. 403–412). Springer Verlag. https://doi.org/10.1007/978-3-319-11538-2_37
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