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Erschienen in:
Monitoring the Spatial Correlation Among Functional Data Streams Through Moran’s Index Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

User Profile Construction Method for Personalized Access to Data Sources Using Multivariate Conjoint Analysis and Collaborating Filtering

verfasst von : Oumayma Banouar, Said Raghay

Erschienen in: New Statistical Developments in Data Science

Verlag: Springer International Publishing

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Abstract

Current information systems provide access to multiple, distributed, autonomous and potentially redundant data sources. Their users may not know the sources they questioned, nor their description and content. Consequently, their queries reflect no more a need that must be satisfied but an intention that must be refined. The purpose of personalization is to facilitate the expression of users’ needs. It allows them to obtain relevant information by maximizing the exploitation of their preferences grouped in their respective profile. In this work, we present a collaborative filtering method based on a Multivariate Conjoint Analysis approach to get these profiles. The proposed strategy provides a representation of the users and of the items, according to their characteristics, on factorial plans; whereas, the collaborative approach predicts the missing preferences.

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Vorheriges Kapitel Monitoring the Spatial Correlation Among Functional Data Streams Through Moran’s Index
Nächstes Kapitel Clustering Communities Using Interval K-Means
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Metadaten
Titel
User Profile Construction Method for Personalized Access to Data Sources Using Multivariate Conjoint Analysis and Collaborating Filtering
verfasst von
Oumayma Banouar
Said Raghay
Copyright-Jahr
2019
Buch
New Statistical Developments in Data Science

Print ISBN: 978-3-030-21157-8

Electronic ISBN: 978-3-030-21158-5

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-030-21158-5_2

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