Abstract
So far several methods have been proposed for clustering the web. On the other hand, many algorithms have been developed for clustering the relational data, but their usage for the Web is to be investigated. One main category of such algorithms is density based methods providing high quality results. In this paper first, a new density based algorithm is introduced and then it is compared with other algorithms of this category. The proposed algorithm has some interesting properties and capabilities such as hierarchical clustering and sampling, making it suitable for clustering the web data.
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Chehreghani, M.H., Abolhassani, H., Chehreghani, M.H. (2007). Attaining Higher Quality for Density Based Algorithms. In: Marchiori, M., Pan, J.Z., Marie, C.d.S. (eds) Web Reasoning and Rule Systems. RR 2007. Lecture Notes in Computer Science, vol 4524. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72982-2_27
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DOI: https://doi.org/10.1007/978-3-540-72982-2_27
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