Clustering-based incremental web crawling
ACM Transactions on Information Systems (TOIS)
Finding potential seeds through rank aggregation of web searches
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
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This paper identifies and explores the problem of seed selection in a web-scale crawler. We argue that seed selection is not a trivial but very important problem. Selecting proper seeds can increase the number of pages a crawler will discover, and can result in a collection with more ``good" and less "bad" pages. Based on the analysis of the graph structure of the web, we propose several seed selection algorithms. Effectiveness of these algorithms is proved by our experimental results on real web data.