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Biogeography optimization algorithm based next web page prediction using weblog and web content features

Gangurde, Roshan AnantKumar, Binod
IAES International Journal of Artificial Intelligence (IJ-AI) (Sinta 1)Vol. 0 No. 01 Juni 2020
DOI10.11591/ijai.v9.i2.pp327-335

Abstrak

Recommendation of web page as per users’ interest is a broad and important area of research. Researcher adopts user behavior from actions present in cookies, logs and search queries. This paper has utilized a prior webpage fetching model using web page prediction. For this purpose, web content in form of text and weblog features are analyzed. As per dynamic user behavior, proposed model LWPP-BOA (Logistic Web Page Prediction By Biogeography Optimization Algorithm) predict page by using genetic algorithm. Based on user actions, weblog feature are developed in form of association rules, while web content gives a set of relevant text patterns. Page prediction as per random user behavior is enhanced by means of Biogeography Optimization Algorithm where crossover operation is performed as per immigration and emigration values. Here population updation depends on other parameters of chromosome except fitness value. Experiments are conducted on real dataset having web content and weblogs. Results are compared using precision, coverage, M-Metric, MAE and RMSE parameters and it indicates that the proposed work is better than other approaches already in use.

Kata Kunci

Genetic AlgorithmAssociation Rule MiningLogistic Regression

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Biogeography optimization algorithm based next web page prediction using weblog and web content features | IAES International Journal of Artificial Intelligence (IJ-AI) | Publiora