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2018 | OriginalPaper | Chapter

Statistical Methods for Use in Analysis of Trust-Skyline Sets

Authors : Amna Abidi, Mohamed Anis Bach Tobji, Allel Hadjali, Boutheina Ben Yaghlane

Published in: Enterprise Information Systems

Publisher: Springer International Publishing

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Abstract

Volume and veracity of Resource Description Framework (RDF) data in the web are two main issues in managing information. Due to the diversity of RDF data, several researchers enriched the basic RDF data model with trust information to rate the trustworthiness of the collected data.

This paper is an extension of our previous work in which we extended Trust-Skyline queries over RDF data. We are interested in analyzing the trust-Skyline list. We particularly study the user-defined trust measure (\(\alpha \)) problem, which consists in checking the impact of such measure on the resulting list. To this end, we first distinguish between the trust-Skyline points, we propose two main categories, points that enter to the final list after the Pareto-dominance check and points that have trust measures less than \(\alpha \).

Then, we proposed statistical methods to investigate the trust measures dependence. Indeed we used the central tendency measures, and the measures of spread for such analysis. Experiments led on the algorithm’s implementations showed promising results.

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previous chapter Towards Generating Spam Queries for Retrieving Spam Accounts in Large-Scale Twitter Data

next chapter Enabling Semantics in Enterprises

The physical data model used in this article is an extension of the 3Store model presented in [15, 23].

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Title: Statistical Methods for Use in Analysis of Trust-Skyline Sets
Authors: Amna Abidi
Mohamed Anis Bach Tobji
Allel Hadjali
Boutheina Ben Yaghlane
Publisher: Springer International Publishing
Book: Enterprise Information Systems
Print ISBN: 978-3-319-93374-0

Electronic ISBN: 978-3-319-93375-7

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-93375-7_19

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