Monitoring Recommender Systems: A Business Intelligence Approach

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Catarina Felix (Author) Other; Carlos Soares (Author) FEUP; Alipio Jorge (Author) FCUP; Joao Vinagre (Author) Other

Conference proceedings International

Title: COMPUTATIONAL SCIENCE AND ITS APPLICATIONS, PART VI - ICCSA 2014

Pages: 277-288

14th International Conference on Computational Science and Its Applications (ICCSA)

Guimaraes, PORTUGAL, JUN 30-JUL 03, 2014

Indexing

ISI Web of Knowledge - 2 Citations

Scopus - 2 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-009-Q3P

DOI: 10.1007/978-3-319-09153-2_21

Abstract (EN): Recommender systems (RS) are increasingly adopted by e-business, social networks and many other user-centric websites. Based on the user's previous choices or interests, a RS suggests new items in which the user might be interested. With constant changes in user behavior, the quality of a RS may decrease over time. Therefore, we need to monitor the performance of the RS, giving timely information to management, who can than manage the RS to maximize results. Our work consists in creating a monitoring platform - based on Business Intelligence (BI) and On-line Analytical Processing (OLAP) tools - that provides information about the recommender system, in order to assess its quality, the impact it has on users and their adherence to the recommendations. We present a case study with Palco Principal(1), a social network for music.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 12