Incremental web-site boundary detection using random walks
Machine Learning and Data Mining in Pattern Recognition: 7th International …, 2011•Springer
The paper describes variations of the classical k-means clustering algorithm that can be
used effectively to address the so called Web-site Boundary Detection (WBD) problem. The
suggested advantages offered by these techniques are that they can quickly identify most of
the pages belonging to a web-site; and, in the long run, return a solution of comparable (if
not better) accuracy than other clustering methods. We analyze our techniques on artificial
clones of the web generated using a well-known preferential attachment method.
used effectively to address the so called Web-site Boundary Detection (WBD) problem. The
suggested advantages offered by these techniques are that they can quickly identify most of
the pages belonging to a web-site; and, in the long run, return a solution of comparable (if
not better) accuracy than other clustering methods. We analyze our techniques on artificial
clones of the web generated using a well-known preferential attachment method.
Abstract
The paper describes variations of the classical k-means clustering algorithm that can be used effectively to address the so called Web-site Boundary Detection (WBD) problem. The suggested advantages offered by these techniques are that they can quickly identify most of the pages belonging to a web-site; and, in the long run, return a solution of comparable (if not better) accuracy than other clustering methods. We analyze our techniques on artificial clones of the web generated using a well-known preferential attachment method.
Springer
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