An Adapted Approach for User Profiling in a Recommendation System: Application to Industrial Diagnosis

TitleAn Adapted Approach for User Profiling in a Recommendation System: Application to Industrial Diagnosis
Publication TypeJournal Article
Year of Publication2018
AuthorsBenkaddour, F. Z., N. Taghezout, F. Z. Kaddour-Ahmed, and I. - A. Hammadi
JournalInternational Journal of Interactive Multimedia and Artificial Intelligence
ISSN1989-1660
IssueRegular Issue
Volume5
Number3
Date Published12/2018
Pagination118-130
Abstract

In this paper, we propose a global architecture of a recommender tool, which represents a part of an existing collaborative platform. This tool provides diagnostic documents for industrial operators. The recommendation process considered here is composed of three steps: Collecting and filtering information; Prediction or recommendation step; evaluating and improvement. In this work, we focus on collecting and filtering step. We mainly use information result from collaborative sessions and documents describing solutions that are attributed to the complex diagnostic problems. The developed tool is based on collaborative filtering that operates on users' preferences and similar responses.

KeywordsCollaborative Filtering, DSS, Industrial Diagnosis, Recommendation Systems, Twitter
DOI10.9781/ijimai.2018.06.003
URLhttp://www.ijimai.org/journal/sites/default/files/files/2018/06/ijimai_5_3_13_pdf_15716.pdf
AttachmentSize
ijimai_5_3_13.pdf1.35 MB