Hopfilter: an agent for filtering web pages based on the hopfield artificial neural network model

Authors:
Juan Manuel Adán-Coello;Carlos Miguel Tobar;Ricardo Luís de Freitas;Armando Marin
Affiliations:
PUC-Campinas, Campinas, SP, Brazil;PUC-Campinas, Campinas, SP, Brazil;PUC-Campinas, Campinas, SP, Brazil;Senac Ribeirão-Preto, Ribeirão Preto, SP, Brazil
Venue:
BNCOD'07 Proceedings of the 24th British national conference on Databases
Year:
2007

Citing 5
Cited 1

Another stemmer

ACM SIGIR Forum
Automatic concept classification of text from electronic meetings

Communications of the ACM
The SMART and SIRE experimental retrieval systems

Readings in information retrieval
The SIFT information dissemination system

ACM Transactions on Database Systems (TODS)
Information Retrieval

Information Retrieval

Personalized web page filtering using a hopfield neural network

ICANN'07 Proceedings of the 17th international conference on Artificial neural networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

With the expansion of the Internet, the amount of information available is continuously reaching higher growth rates. This fact leads to the necessity of developing new advanced tools to collect and filter information that meets users' preferences. This paper presents an agent that uses automatic indexing, concept space generation, and a Hopfield artificial neural network to filter web pages according to users' interests. The experiments that were conducted to evaluate the agent show that it has very satisfactory precision and coverage rates.