Building Customized Search Engines

Chua, Cecil Eng Huang; Chiang, Roger H. L.

doi:10.4018/jiit.2009070101

Cited by 10 publications

(2 citation statements)

References 46 publications

(73 reference statements)

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“…The search engine performance is mostly depends on the searching scenario and the information needs of the user (Hamdi et al, 2008;Meng et al, 2007). A significant number of search engines consolidating algorithms to bolster an assortment of information search needs (Chua et al, 2009;Zhang & Sugumaran, 2014). The greater part of the search engine utilize Page rank algorithms, which can devise the documents all together of their importance, significance and content score.…”

Section: Related Workmentioning

confidence: 99%

Ranking Pages of Clustered Users using Weighted Page Rank Algorithm with User Access Period

Sumathi

Sendhilkumar

Mahalakshmi

2015

International Journal of Intelligent Information Technologies

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The World Wide Web comprises billions of web pages and a tremendous amount of information accessible inside of web pages. To recover obliged data from the World Wide Web, search engines perform number of tasks in light of their separate structural planning. The point at which a user gives a query to the search engine, it commonly returns a bulky number of pages related to the user's query. To backing the users to explore in the returned list, different ranking techniques are connected on the search results. The vast majority of the ranking calculations, which are given in the related work, are either link or content based. The existing works don't consider user access patterns. In this paper, a page ranking approach of Weighted Page Rank Score Algorithm taking user access is being conceived for search engines, which deals with the premise of weighted page rank method and considers user access period of web pages into record. For this reason, the web users are clustered based on the Particle Swarm Optimization (PSO) approach. From those groups, the pages are ranked by improving the weighted page rank approach with usage based parameter of user access period. This calculation is utilized to discover more applicable pages as per user's query. In this way, this idea is extremely helpful to show the most important pages on the uppermost part of the search list on the principle of user searching behavior, which shrinks the search space on a huge scale.

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Section: Related Workmentioning

confidence: 99%

Ranking Pages of Clustered Users using Weighted Page Rank Algorithm with User Access Period

Sumathi

Sendhilkumar

Mahalakshmi

2015

International Journal of Intelligent Information Technologies

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“…The framework of fuzzy classified association rule mining is presented which incorporates fuzzy set modeling based on the time in an existing association rule mining technique (Kumar & Thambidurai, 2004;Lei, Kang, Lu, & Yan, 2005). Interoperability architecture for building customized search engines is developed by Cecil et al Through this, the existing search engines are decomposed into self-contained components (Chua, Chiang, & Storey, 2009).…”

Section: Introductionmentioning

confidence: 99%

Intelligent Information Retrieval Using Fuzzy Association Rule Classifier

Sankaradass

Kannan

2011

International Journal of Intelligent Information Technologies

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As the use of web applications increases, when users use search engines for finding some information by inputting keywords, the number of web pages that match the information increases at a tremendous rate. It is not easy for a user to retrieve the exact web page which contains information he or she requires. In this paper, an approach to web page retrieval system using the hybrid combination of context based and collaborative filtering method employing the concept of fuzzy association rule classification is introduced and the authors propose an innovative clustering of user profiles in order to reduce the filtering space and achieves sub-linear filtering time. This approach can produce recommended web page links for users based on the information that associates strongly with users’ queries quickly with better efficiency and therefore improve the recall, precision of a search engine.

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