The Strategy on Replicate and Similar Web Collections' Detecting and Clustering
The fraction of the web collections consisting of duplicates has been surveyed at a high level. The quality of a web crawler increases if it can assess whether a newly crawled web page is a duplicate of a previously crawled page, so the strategy on detecting and filtering duplicates is important to improve the performance of search engine. This paper first presents the algorithm based on URL hashing to filter duplicates. On the basis of the Chinese key-concepts weighting and extracting, this paper then proposes a method to cluster similar results based on content analysis. Both the experimental results and the application validate the feasibility of the approach as this can minimize the overlap while clustering similar results effectively. Some existing problems and further works are also present in the end. (C) 2009 Wiley Periodicals, Inc. Comput Appl Eng Educ 20: 221-231, 2012; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.20388
clustering search engine hash function key-concept string