Authors:
Felipe Mancini
;
Alex Esteves Jaccoud Falcão
;
Anderson Diniz Hummel
;
Thiago Martini Costa
;
Cristina Lucia Feijo Ortolani
;
Fabio Teixeira
and
Ivan Torres Pisa
Affiliation:
Federal University of São Paulo, Brazil
Keyword(s):
Internet, health, Information storage and retrieval, Pattern recognition system.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Cloud Computing
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
e-Health
;
Enterprise Information Systems
;
Expert Systems
;
Health Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Platforms and Applications
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Symbolic Systems
Abstract:
The increase in the amount of available information on the world wide web is inexorable, which, on one hand, provides the web user with more information. On the other hand, however, web searches become increasingly more difficult to handle due to the increasing number of retrieved documents. The present study is a proposal of development for a Brazilian search portal specific for health-related content. The aim of such development is to provide web users, mainly the non-specialist ones, with the largest number possible of web pages relevant to their search terms and inferred search intentions. The proposed search portal integrates web mining-based filters and a decision-making support tool. The preliminary study results show that among the algorithms tested to incorporate a filter module specific for health-related content - artificial neural networks, logistic regression and nearest neighbor clustering (NNC) -, the application of NNC resulted in the automated web health-related cont
ent classifier with the best performance for sensitivity and specificity 0.92 and 1.00 respectively.
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