{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T23:36:31Z","timestamp":1764977791708,"version":"3.46.0"},"reference-count":22,"publisher":"Walter de Gruyter GmbH","issue":"2","license":[{"start":{"date-parts":[[2017,1,13]],"date-time":"2017-01-13T00:00:00Z","timestamp":1484265600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,3,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Several users use metasearch engines directly or indirectly to access and gather data from more than one data source. The effectiveness of a metasearch engine is majorly determined by the quality of the results it returns in response to user queries. The rank aggregation methods that have been proposed until now exploit a very limited set of parameters, such as total number of used resources and the rankings they achieved from each individual resource. In this paper, we use the fuzzy-bat to merge the score computation module effectively. Initially, we give a query to different search engines we use and the top\n                    <jats:italic>n<\/jats:italic>\n                    list from each search engine is chosen for further processing our technique. We then merge the top\n                    <jats:italic>n<\/jats:italic>\n                    list based on unique links, and we do some parameter calculations such as title-based calculation, snippet-based calculation, content-based calculation, address-based calculation, link-based calculation, uniform resource locator-based calculation, and co-occurrence-based calculation. We give the solutions of the calculations with the user given the ranking of links to the fuzzy-bat to train the system. The system then ranks and merges the links we obtain from different search engines for the query we give.\n                  <\/jats:p>","DOI":"10.1515\/jisys-2016-0157","type":"journal-article","created":{"date-parts":[[2017,1,13]],"date-time":"2017-01-13T05:01:38Z","timestamp":1484283698000},"page":"249-262","source":"Crossref","is-referenced-by-count":1,"title":["Utilization of Co-occurrence Pattern Mining with Optimal Fuzzy Classifier for Web Page Personalization"],"prefix":"10.1515","volume":"27","author":[{"given":"Pappu","family":"Srinivasa Rao","sequence":"first","affiliation":[{"name":"Jawaharlal Nehru Technological University , Hyderabad , India"}]},{"given":"Devara","family":"Vasumathi","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering , Jawaharlal Nehru Technological University , Hyderabad , India"}]}],"member":"374","published-online":{"date-parts":[[2017,1,13]]},"reference":[{"key":"2025120523303651672_j_jisys-2016-0157_ref_001_w2aab3b7c10b1b6b1ab1b6b1Aa","unstructured":"J. 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