A GP-adaptive web ranking discovery framework based on combinative content and context features

Keyhanipour, Amir Hosein; Piroozmand, Maryam; Badie, Kambiz

doi:10.1016/j.joi.2008.11.006

Cited by 6 publications

(1 citation statement)

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“…Link analysis is a method for determining which pages are good for particular topics based on both the quantity and quality of links pointing to that document. PageRank is a link analysis algorithm, named after Larry Page and used by the Google Internet search engine, that assigns a numerical weighting to each element of a hyperlinked set of documents [16]. hyperlink-induced topic search (HITS) is a link analysis algorithm that developed by Jon Kleinberg.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Web Usage Mining Approach Using Chaos Optimization and Particle Swarm Optimization Algorithm Based on Optimal Feedback Model

Dai

Wang

Shu

2013

Mathematical Problems in Engineering

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The dynamic nature of information resources as well as the continuous changes in the information demands of the users has made it very difficult to provide effective methods for data mining and document ranking. This paper proposes an efficient particle swarm chaos optimization mining algorithm based on chaos optimization and particle swarm optimization by using feedback model of user to provide a listing of best-matching webpages for user. The proposed algorithm starts with an initial population of many particles moving around in aD-dimensional search space where each particle vector corresponds to a potential solution of the underlying problem, which is formed by subsets of webpages. Experimental results show that our approach significantly outperforms other algorithms in the aspects of response time, execution time, precision, and recall.

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Section: Related Workmentioning

confidence: 99%