Abstract
In this paper, we propose four specifications which can be used for the evaluation of community identification algorithms. Furthermore, a novel algorithm VHITS meeting the four established specifications is presented. Basically, VHITS is based on a two-step approach. In the first step, the Nonnegative Matrix Factorization is used to estimate the community memberships. In the second step, a voting scheme is employed to identify the hubs and authorities of each community. VHITS is then compared to the HITS and PHITS algorithms. Experimental results show that VHITS is more adapted than HITS and PHITS to the task of community identification in citation networks.
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Chikhi, N.F., Rothenburger, B., Aussenac-Gilles, N. (2008). A New Algorithm for Community Identification in Linked Data. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85563-7_81
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DOI: https://doi.org/10.1007/978-3-540-85563-7_81
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85562-0
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