Fast blocking of undesirable web pages on client PC by discriminating URL using neural networks

Ma, Huadóng

doi:10.1016/j.eswa.2007.01.023

Cited by 4 publications

(1 citation statement)

References 20 publications

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“…However it is not possible to increase the accuracy of web classification due to the diversity in the web pages' content. Neural network can be used to filter the data on the web for classification [2,8,11,14,19,21,23].…”

Section: Neural Network Methodologymentioning

confidence: 99%

Neural Network based Approach for Predicting user Satisfaction with Search Engine

Yadav¹,

Sangwan²

2011

IJCA

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Success of a search engine is measured by the satisfaction of its users. Finding user expectation can be a better step for improved user satisfaction. In this paper we have proposed a neural network based approach for predicting user satisfaction with search engine. Our work is divided in two parts. Part I investigates user expectations towards search engine for their information need. In Part II we proposed an Artificial Neural Network (ANN) model for predicting User Satisfaction. In our work we have analyzed the major factors affecting user satisfaction with search engine and find out the importance /priority value of these factors based on a survey conducted on 100 search engine users of different profiles with 5-10 years of experience using search engines for their information needs like study material, entertainment, research, day to day problem solution etc. In the present work we have identified four major factors namely up-to-date information, search result relevancy, response time and reliability, contributing to the user satisfaction and developed an ANN model which predicts satisfaction results with a reasonable degree of accuracy.

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