Process Mining for Recommender Strategies Support in News Media

Elena Viorica Epure 1 Jon Ingvaldsen 2 Rebecca Deneckere 1 Camille Salinesi 1
1 CRI - Centre de Recherche en Informatique de Paris 1
2 NTNU - Norwegian University of Science and Technology [Trondheim]
Abstract : The strategic transition of media organizations to personalized information delivery has urged the need for richer methods to analyze the customers. Though useful in supporting the creation of recommender strategies, the current data mining techniques create complex models requiring often an understanding of techniques in order to interpret the results. This situation together with the recommender technologies deluge and the particularities of the news industry pose challenges to the news organization in making decisions about the most suitable strategy. Therefore, we propose process mining as a high-level, end-to-end solution to provide insights into the consumers' behavior and content dynamics. Specifically, we explore if it allows news organizations to analyze independently and effectively their data in order to support them in defining recommender strategies. The solution was implemented in a case study with the third largest news provider in Norway and yielded preliminary positive results. To our knowledge, this is the first attempt to apply a process mining methodology and adapt the techniques to support media industry with the recommender strategies.
Keywords : news media case study process mining methodology intention mining process mining intentional process models behavioral analysis recommender strategies
Type de document :
Communication dans un congrès
IEEE Tenth International Conference on Research Challenges in Information Science (IEEE RCIS 2016), Jun 2016, Grenoble, France. 2016
Liste complète des métadonnées

Littérature citée [42 références]  Voir  Masquer  Télécharger
https://hal-paris1.archives-ouvertes.fr/hal-01316566
Contributeur : Elena Epure <>
Soumis le : lundi 30 mai 2016 - 15:53:09
Dernière modification le : jeudi 2 juin 2016 - 01:04:25
Document(s) archivé(s) le : mercredi 31 août 2016 - 10:19:25

Fichier

Rcis2016_Final_Revised.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01316566, version 1

Collections

UNIV-PARIS1 | TICE | CRI

Citation

Elena Viorica Epure, Jon Ingvaldsen, Rebecca Deneckere, Camille Salinesi. Process Mining for Recommender Strategies Support in News Media. IEEE Tenth International Conference on Research Challenges in Information Science (IEEE RCIS 2016), Jun 2016, Grenoble, France. 2016. 〈hal-01316566〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

189

Téléchargements de fichiers

506

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD