Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen


Reiter-Haas Markus, Slawicek Valentin, Lacic Emanuel

Studo Jobs: Enriching Data With Predicted Job Labels

ACM, Graz, 2017


Lacic Emanuel, Kowald Dominik, Lex Elisabeth

Tailoring Recommendations for a Multi-Domain Environment

ACM International Conference on Recommender Systems 2017, RecSys'2017, ACM, Como, Italy, 2017

Recommender systems are acknowledged as an essential instrumentto support users in finding relevant information. However,the adaptation of recommender systems to multiple domain-specificrequirements and data models still remains an open challenge. Inthe present paper, we contribute to this sparse line of research withguidance on how to design a customizable recommender systemthat accounts for multiple domains with heterogeneous data. Usingconcrete showcase examples, we demonstrate how to setup amulti-domain system on the item and system level, and we reportevaluation results for the domains of (i) LastFM, (ii) FourSquare,and (iii) MovieLens. We believe that our findings and guidelinescan support developers and researchers of recommender systemsto easily adapt and deploy a recommender system in distributedenvironments, as well as to develop and evaluate algorithms suitedfor multi-domain settings
Kontakt Karriere

Hiermit erkläre ich ausdrücklich meine Einwilligung zum Einsatz und zur Speicherung von Cookies. Weiter Informationen finden sich unter Datenschutzerklärung

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.