ConRec: A Recommender System featuring Spatial, Temporal, and Personal Context


The thesis aims at designing a prototype Recommender System (ConRec) able to give recommendation messages regarding healthcare domain influenced by the spatial, temporal, and personal (preferences, clinical data, etc.) context of the target patient.

Keywords:  recommender systems, recommendation, context

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Thesis

Supervision

— supervisor
Andrea Omicini
— co-supervisor
Stefano Mariani

Category

2nd-Cycle Thesis

Status

out-of-date

Language

wgb.gif

Dates

— available since
15/03/2018

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