NDLI: Improvement of Collaborative Filtering Systems through Resource Description Framework

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Improvement of Collaborative Filtering Systems through Resource Description Framework

Content Provider	ACM Digital Library
Author	Sahraoui, Kharroubi Youcef, Dahmani Omar, Nouali
Abstract	The huge mass of data generated continuously leads to information overload which limit the tools available to manage, store and secure this traffic on the web. The situation is paradoxical, a need for timely relevant information and the difficulty to btain this information because it is lost in the mass. The use of fully search engine based on the formulation of the request by users show some limitations. The trend is to improve the information filtering approaches to better answer the user's expectations. In this work, we modelled a collaborative filtering system by Friend Of A Friend (FOAF) formalism for the representation of the users and the Dublin Core (DC) vocabulary to represent the resources " items". In addition, and to ensure the interoperability and openness of this model, we adopted the Resource Description Framework (RDF) syntax to describe the various modules of the system. A hybrid function was introduced for the calculation of prediction. The empirical tests on various real data sets (Book-Crossing, FoafPub) showed satisfactory performances in relevance and precision.
Starting Page	1
Ending Page	5
Page Count	5
File Format	PDF
ISBN	9781450334587
DOI	10.1145/2816839.2816863
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-11-23
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Similarity Big data User profile Web resources Recommendation
Content Type	Text
Resource Type	Article

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