1st International Workshop on Management of User-Generated Data (MUSD)
September 8, 2019 - Bled, Slovenia colocated with ADBIS 2019
The field of recommender systems (RecSys) is focused on using structured data for generating recommendations of items that could be useful for end users. However, this structured data is not something that is available out of the box. The data about users is acquired at different stages of the user interaction and has to be properly managed, processed, and structured in order to be ready for RecSys algorithms.
The aim of this workshop is to bring together experts from the fields of data management and recommender systems to discuss issues that lie at the intersection of both research areas. Expertise from data management should inform experts from recommender systems to design their algorithms in a more efficient way, and vice versa: recommender system experts should inform data management experts of open performance issues in RecSys algorithms. In this way the workshop will open new research avenues for researches from both domains.
The workshop will have a hybrid format; the prospective authors are encouraged to submit either (i) technical papers or (ii) white papers/position statements. Based on the number of submissions the workshop will be divided into (i) the mini-conference part around the technical papers and (ii) the more interactive session(s) around the position papers in the form of working group meetings organized around specific topics emerged from the white papers.
Important dates
Paper submission: May 17, 2019Acceptance notification: June 10, 2019
Camera ready: June 23, 2019
Workshop: September 8, 2019
Venue
See ADBIS 2019 conference website: https://adbis2019.um.si/Topics of interest
Topics of particular interest include the intersection of RecSys and data management including, but not limited to:
- open issues in data management for recsys algorithms
- management of personalization data
- management of user data
- time series user data
- time series clustering
- pattern matching of user data
- distributed storage of user data
- privacy and security of user data
- temporal social networks
- modeling, mining and querying user-generated content
- wearable Sensor databases and mobile data management
- user interfaces and visualization of user data
- data extraction and cleaning
Submission instructions
The workshop welcomes long paper, short paper, and position paper submissions. The page limit for long papers is 12 pages and 6 pages for short and position papers. Papers should be prepared according to the LNCS format (templates are available here). Latex submissions are highly encouraged. Nonetheless, papers prepared in other word processing software are also welcome. Papers should be submitted in PDF format via Easychair: https://easychair.org/conferences/?conf=musd2019.Workshop chairs
Anton Dignös, Free University of Bozen Bolzano, ItalyMarko Tkalcic, Free University of Bozen Bolzano, Italy
Program Committee
Francesco Barile (Free University of Bozen Bolzano, Italy)Theodoros Chondrogiannis (University of Konstanz, Germany)
Amra Delic (TU Wien, Austria)
Mehdi Elahi (Free University of Bozen Bolzano, Italy)
Bruce Ferwerda (Jonkoping University, Sweden)
Boris Glavic (Illinois Institute of Technology, USA)
Mark Graus (University of Maastricht, Netherlands)
Peter Knees (TU Wien, Austria)
Michele Linardi (LIPADE, Paris Descartes University, France)
Tomasz Miksa (TU Wien/SBA Research, Austria)
Thuy Ngoc Nguyen (Free University of Bozen Bolzano, Italy)
Markus Schedl (JKU Linz, Austria)
Christoph Trattner (University of Bergen, Norway)
Proceedings
Workshop papers will be published by Springer in the Communications in Computer and Information Science (CCIS) book series. The Springer CCIS volume with workshop papers will be published only as a DIGITAL volume, available for downloading from the Springer portal.
The best workshop papers will be invited for publications in the following journals:
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Computer Science and Information Systems http://www.comsis.org/
5-year IF: 0.675, indexed by: Science Citation Index (SCI) by Thomson Reuters, SCOPUS (Elsevier), Summon (Serials Solutions) -
Journal on Data Semantics (Springer)
DBLP, Emerging Sources Citation Index