LEARning Next gEneration Rankers (LEARNER 2017)

Nicola Ferro, Claudio Lucchese, Maria Maistro, Raffaele Perego

Abstract

The aim of LEARNER@ICTIR2017 is to investigate new solutions for LtR. In details, we identify some research areas related to LtR which are of actual interest and which have not been fully explored yet. We solicit the submission of position papers on novel LtR algorithms, on evaluation of LtR algorithms, on dataset creation and curation, and on domain specific applications of LtR. LEARNER@ICTIR2017 will be a gathering of academic people interested in IR, ML and related application areas. We believe that the proposed workshop is relevant to ICTIR since we look for novel contributions to LtR focused on foundational and conceptual aspects, which need to be properly framed and modeled.

OriginalsprogEngelsk
TitelICTIR 2017 - Proceedings of the 2017 ACM SIGIR International Conference on the Theory of Information Retrieval
Antal sider2
ForlagAssociation for Computing Machinery, Inc.
Publikationsdato1 okt. 2017
Sider331-332
ISBN (Elektronisk)9781450344906
DOI
StatusUdgivet - 1 okt. 2017
Udgivet eksterntJa
Begivenhed7th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2017 - Amsterdam, Holland
Varighed: 1 okt. 20174 okt. 2017

Konference

Konference7th ACM SIGIR International Conference on the Theory of Information Retrieval, ICTIR 2017
Land/OmrådeHolland
ByAmsterdam
Periode01/10/201704/10/2017
SponsorACM Special Interest Group on Information Retrieval (SIGIR)

Citationsformater