NewsKDD 2014 - Workshop on Data Science for News Publishing (NewsKDD)

Data Science for News Publishing (NewsKDD)
http://ailab.ijs.si/~blazf/NewsKDD2014/
at KDD 2014, New York, United States,
August 24, 2014
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Submission page: https://www.easychair.org/conferences/?conf=newskd...
IMPORTANT DATES
- Submission Date: June 24, 2014
- Notification of Acceptance: July 8, 2014
- Workshop date: Sunday, August 24, 2014
DESCRIPTION
News publishing is a domain with a lot of specifics related to data processing
spanning interdisciplinary across many fields of data related research. The aim
of this workshop is to cover data analytic/mining research, approaches and
solutions for numerous data challenges related to news publishing. The key
categories of data analytic challenges in news publishing include areas like:
- editorial support (media monitoring, data journalism, news bias),
- content management (search, ranking, semantics),
- user management (user profiling, recommendation, social media),
- visualization,
- archives,
- standardization, and
The workshop will be structured as a set of sections including: what news
publishers' R&Ds are doing, live system demos, contributed short papers,
invited talks, and the panel. The workshop will be video-recorded and
published on videolectures.net.
Target audience will be data researchers and professionals from publishing
industry (being extensively present in New York). Some of the categories include:
- Data scientists from publishing houses of all types
- Journalists, editors and bloggers operating in online publishing
- Data Journalists and Info-graphics creators
- Software engineers from publishing houses or vendor companies
- Researchers and students in social sciences related to news domain
- Broader public interested in advances in data analytics for news publishing
SUBMISSION INSTRUCTIONS
We invite the submission of extended abstracts on all aspects of text
understanding, and we suggest keeping the paper under 4 pages (NOT including
references). For projects that require more room for descriptions, we encourage
the authors to include details of the work as an appendix and/or other
supplementary materials. Please use the KDD style files and formatting
instructions. The submissions should include the authors' names and
affiliations since the review process will not be double blind. Topics that
were recently published or presented elsewhere are allowed, provided that the
extended abstract mentions this explicitly; topics that were presented in
non-machine learning and non-data mining conferences are especially encouraged.
Accepted submissions will be presented either as contributed talks or as posters.
In both cases use the Easychair submission site to upload your paper. We will
pursue a journal special issue with the topics of the workshop if we receive an
appropriate number of high-quality submissions.
Submission page: https://www.easychair.org/conferences/?conf=newskd...
ORGANIZERS
- Marko Grobelnik, Jozef Stefan Institute, Slovenia
- Blaz Fortuna, Jozef Stefan Institute, Slovenia
- James Hodson, Bloomberg, New York
- Evan Sandhaus, New York Times, New York