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Full-Text Articles in Databases and Information Systems
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Automatically Discovering The Number Of Clusters In Web Page Datasets, Zhongmei Yao
Computer Science Faculty Publications
Clustering is well-suited for Web mining by automatically organizing Web pages into categories, each of which contains Web pages having similar contents. However, one problem in clustering is the lack of general methods to automatically determine the number of categories or clusters. For the Web domain in particular, currently there is no such method suitable for Web page clustering. In an attempt to address this problem, we discover a constant factor that characterizes the Web domain, based on which we propose a new method for automatically determining the number of clusters in Web page data sets. We discover that the …
Discovering Informative Subgraphs In Rdf Graphs, William H. Milnor, Cartic Ramakrishnan, Matthew Perry, Amit P. Sheth, John A. Miller, Krzysztof Kochut
Discovering Informative Subgraphs In Rdf Graphs, William H. Milnor, Cartic Ramakrishnan, Matthew Perry, Amit P. Sheth, John A. Miller, Krzysztof Kochut
Kno.e.sis Publications
Discovering patterns in graphs has long been an area of interest. In most contemporary approaches to such pattern discovery either quantitative anomalies or frequency of substructure is used to measure the interestingness of a pattern. In this paper we address the issue of discovering informative sub-graphs within RDF graphs. We motivate our work with an example related to Semantic Search. A user might pose a question of the form: ' What are the most relevant ways in which entity X is related to entity Y?' the response to which is a subgraph connecting X to Y. Relevance of the …