CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
thesis
Data-Driven Recommender Systems: Sequences of recommendations
Authors
Jérémie Mary
Publication date
24 November 2015
Publisher
HAL CCSD
Abstract
This document is about some scalable and reliable methods for recommender systems from a machine learner point of view. In particular it adresses some difficulties from the non stationary case
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Hal-Diderot
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:HAL:tel-01374729v1
Last time updated on 14/04/2021
HAL Descartes
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:HAL:tel-01374729v1
Last time updated on 14/04/2021
INRIA a CCSD electronic archive server
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:HAL:tel-01374729v1
Last time updated on 09/11/2016
Thèses en Ligne
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:HAL:tel-01374729v1
Last time updated on 08/11/2016