JUMPERS: Jobzippers User-driven Multi-relational and Personalized Recommender System

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Forschungsstelle

INNOSUISSE

Projektnummer

12167.2;5 PFES-ES

Projekttitel

JUMPERS: Jobzippers User-driven Multi-relational and Personalized Recommender System

Projekttitel Englisch

JUMPERS: Jobzippers User-driven Multi-relational and Personalized Recommender System

Texte zu diesem Projekt

	Deutsch	Französisch	Italienisch	Englisch
Kurzbeschreibung	-		-
Abstract	-		-

Erfasste Texte

Kategorie	Text
Kurzbeschreibung (Englisch)	JUMPERS: Jobzippers User-driven Multi-relational and Personalized Recommender System
Kurzbeschreibung (Französisch)	JUMPERS: Jobzippers User-driven Multi-relational and Personalized Recommender System
Abstract (Englisch)	This project aims at designing, validating and implementing a user-driven multi-relational and personalized recommender system for Jobzippers, the European career center network. The customers targeted by this system are university graduates and employers. The main commercial innovation lies in intelligent recommendation relying on contacts established by students and graduates during the course of their studies with professionals, professors, mentors and peers with similar profile and professional interests. The main scientific innovation lies in advanced multirelational and contextual recommendation algorithms.
Abstract (Französisch)	This project aims at designing, validating and implementing a user-driven multi-relational and personalized recommender system for Jobzippers, the European career center network. The customers targeted by this system are university graduates and employers. The main commercial innovation lies in intelligent recommendation relying on contacts established by students and graduates during the course of their studies with professionals, professors, mentors and peers with similar profile and professional interests. The main scientific innovation lies in advanced multirelational and contextual recommendation algorithms.