Case recommender: A flexible and extensible python framework for recommender systems

Arthur Da Costa, Eduardo Fressato, Fernando Neto, Marcelo Manzato, Ricardo Campello

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Abstract

This paper presents a polished open-source Python-based recommender framework named Case Recommender, which provides a rich set of components from which developers can construct and evaluate customized recommender systems. It implements well-known and state-of-the-art algorithms in rating prediction and item recommendation scenarios. The main advantage of the Case Recommender is the possibility to integrate clustering and ensemble algorithms with recommendation engines, easing the development of more accurate and efficient approaches.

OriginalsprogEngelsk
TitelRecSys 2018 - 12th ACM Conference on Recommender Systems
ForlagAssociation for Computing Machinery
Publikationsdato27. sep. 2018
Sider494-495
ISBN (Elektronisk)9781450359016
DOI
StatusUdgivet - 27. sep. 2018
Udgivet eksterntJa
Begivenhed12th ACM Conference on Recommender Systems, RecSys 2018 - Vancouver, Canada
Varighed: 2. okt. 20187. okt. 2018

Konference

Konference12th ACM Conference on Recommender Systems, RecSys 2018
Land/OmrådeCanada
ByVancouver
Periode02/10/201807/10/2018
SponsorACM Special Interest Group on Computer-Human Interaction (SIGCHI)

Bibliografisk note

Publisher Copyright:
© 2018 Copyright held by the owner/author(s).

Fingeraftryk

Dyk ned i forskningsemnerne om 'Case recommender: A flexible and extensible python framework for recommender systems'. Sammen danner de et unikt fingeraftryk.

Citationsformater