Podcast content has become a major channel for information, entertainment, and advertising. Tens of thousands of podcasts are produced on a daily basis. However, whereas traditional media (news, music, and video) has received extensive attention from the data science and machine learning research communities, research into podcast content modeling, recommendation, and interaction is relatively neglected.
The 1st International Workshop on Machine Learning and Data Mining for Podcasts (MLDM4P), collocated with KDD 2018 will bring together researchers and practitioners in machine learning and data science (e.g., speech, music, text, information retrieval, data mining, and recommender systems) with developers and entrepreneurs in podcasting to discuss practical challenges and research opportunities around podcast content modeling, recommendation and interaction. Although speech and music are important ingredients of podcasts, as a medium, podcasts present heterogeneous content, diverse consuming intentions and unique listening behavior. This workshop is a timely venue to engage researchers and practitioners from different fields to discuss the challenges and opportunities of understanding and serving this burgeoning medium.
Topics of interest for the workshop include, but not limited to, the following
Submission deadline: May 8, 2018, 11:59 PM EST
Notification deadline: June 8, 2018, 11:59 PM EST
Workshop Date: August 20, 2018
Authors are encouraged to submit position, ongoing or recent research related to topics of interests. The workshop program committee will consider all submitted papers and will decide which papers are to be presented as oral or poster presentations. Accepted submissions will be considered non-archival and can be submitted elsewhere without modification. Moreover, submissions to the workshop based on recently published work are also acceptable (though authors should explicitly make note of this in their submissions).
Submission format Submitted paper should be up to 3 pages long (not including references). Submissions are not blind: author names and affiliations should appear on the first page. Papers should be formatted using the 2017 ACM Master Article Template. For LaTeX users, choose `format=sigconf`. This is the typical, two-column proceedings-style template. Authors do not need to include terms, keywords, or other front matter in their submissions.
*Instructions adapted from SysML.
Submission Link: https://easychair.org/conferences/?conf=mldm4p
If you have any questions, please contact Longqi Yang