APPLYING LOGISTIC REGRESSION TO RANK CREDIBILITY IN WEB APPLICATIONS

Rafael Lima, Adriano Pereira

Abstract

The popularization of the World Wide Web (WWW) has given rise to new services every day, demanding mechanisms to ensure the credibility of these online services. Since now, little has been done to measure and understand the credibility of this complex Web environment, which itself is a major research challenge. In this work, we use logistic regression to design and evaluate the credibility of a Web application. We call a credibility model a function capable of assigning a credibility value to transaction of a Web application, considering different criteria of this service and its supplier. In order to validate our proposed methodology, we perform experiments using an actual dataset, from which we evaluated different credibility models using distinct types of information sources, and it allows to compare and evaluate these credibility models. The obtained results are very good, showing representative gains, when compared to a baseline. The results show that the proposed methodology are promising and can be used to enforce trust to users of services on the Web.

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Paper Citation


in Harvard Style

Lima R. and Pereira A. (2011). APPLYING LOGISTIC REGRESSION TO RANK CREDIBILITY IN WEB APPLICATIONS . In Proceedings of the 7th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST, ISBN 978-989-8425-51-5, pages 480-485. DOI: 10.5220/0003345104800485


in Bibtex Style

@conference{webist11,
author={Rafael Lima and Adriano Pereira},
title={APPLYING LOGISTIC REGRESSION TO RANK CREDIBILITY IN WEB APPLICATIONS},
booktitle={Proceedings of the 7th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,},
year={2011},
pages={480-485},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003345104800485},
isbn={978-989-8425-51-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 7th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,
TI - APPLYING LOGISTIC REGRESSION TO RANK CREDIBILITY IN WEB APPLICATIONS
SN - 978-989-8425-51-5
AU - Lima R.
AU - Pereira A.
PY - 2011
SP - 480
EP - 485
DO - 10.5220/0003345104800485