GA Based Model for Web Content Mining

Several methods are available for mining frequent patterns in web data, but mostly they suffer from the problem of huge candidate generation and number of database scans. In view of above a genetic based model for mining frequent patterns in web content data. In the proposed genetic operator, crossing over method leads to offspring which must survive the certain fitness test or conditions to become frequent pattern and ancestor for next patterns. In this way the useless individuals or candidates are pruned out thereby reducing the number of candidates for next test. Also this approach requires only one scan of database. Thus this model is able to address the issues of large number of candidate generation and number of database scans.