Submission

Submissions and reviews are handled electronically via EasyChair at the following address: https://easychair.org/conferences/?conf=dlrs2017. Submissions should be prepared in PDF format according to the standard double-column ACM SIG proceedings format. Authors must submit their papers to arxiv.org simultaneously and send the assigned arxiv ID to the organizers via email when it is available. Failing to send the arxiv ID within at most two weeks from the submission deadline will result in the rejection of the paper.

The ideal length of a paper for DLRS 2017 is between 4-8 pages, but submissions have no strict page limits. Although the authors should avoid submitting unnecessarily long papers in order not to overwhelm reviewers.

DLRS 2017 accepts original and novel contributions that are neither published nor under review in other venues. Self publishing of the submitted papers in public repositories is permitted and encouraged. We also encourage authors to make their code and datasets publicly available.

Papers must be electronically submitted through EasyChair by 23:59 (AoE timezone) on the 22nd of June, 2017. The authors must also submit their papers to arxiv.org simultaneously and email the arxiv ID to the organizers on the workshop’s email address.

All papers are peer reviewed by at least 3 members of the Program Committee consisting of researchers of deep learning and recommender systems.

Accepted papers are published in the workshop proceedings and indexed in the ACM Digital Library. Accepted papers are given either an oral or a poster presentation slot at the workshop. At least one author of every accepted paper must attend the workshop and present their work.