LUC 2012: International Workshop on Learning from User-generated Content

We are deeply sorry to announce that the workshop had to be canceled!

in conjunction with
29th International Conference on Machine Learning (ICML 2012)

Date: June 30, 2012

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The International Workshop on Learning from User-generated Content (LUC) serves as a forum for theoretical and practical discussions of cutting edge research on machine learning technologies for multimedia information retrieval. Topics covered include all aspects of machine learning with a relation to social media and user-generated content, in particular, (social) web mining, multimedia information extraction, retrieval, and recommendation as well as mobile applications and services that make use of machine learning and Web technology. Submissions addressing concrete implementations of systems and services by both academic institutions and industrial companies are also welcome.


2012-05-24: Workshop canceled.
2012-05-07: Submission deadline extended to May 17, 2012.
2012-02-09: Website launched.

 Call for Papers

While the amount of user-generated content has been skyrocketing since the advent of social media and social networks, intelligent approaches to process and make sense of these huge masses of data produced by over a billion users are rather rare so far. Hence, we solicit innovative technical papers with a focus on user-generated content and addressing problems in the fields of machine learning, multimedia, or information retrieval. Also contributions that combine two or more of these fields are highly welcome. We invite authors to submit regular technical papers of up to 8 pages as well as short position or demo papers of 2-4 pages. Regardless of their category, submissions must follow the ACM author guidelines. Paper submissions must be original and not submitted to or accepted by any other conference or journal. All submissions to this workshop will be peer-reviewed by at least three Program Committee members. The review process will be double-blind. Proceedings will be released under a Creative Commons license.

Submissions tackling, for example, one of the following challenges are highly welcome:

  • Explore the usage of several types of social data, including ratings, reviews, tags, comments, hyperlinks, geo‐located data, linked data, multimedia items, and playlists.
  • Extract from these raw data several types of knowledge (users and data): relations, user opinions, user preferences, semantic relationships/description of multimedia objects, sentiment analysis, community detection
  • Exploit novel data mining and information retrieval techniques: expert finding, recommendation computation, similarity evaluation, network analysis, information visualization, multimedia retrieval, semantic indexing, evaluation of systems with implicit data from social media, social and human computation
  • Define new information search problems: context‐dependent recommendation, definition of key users, identification of relevant locations, cross‐domain multimedia recommendation, games and multimedia, cross‐modal social content analysis
  • Evaluate the benefits of such techniques: live users experiments, new off‐line evaluation methods

Topics of Interest

Social Media and Network Analysis
Social Media Mining
Influential User Detection and Analysis
Information Extraction and Knowledge Harvesting from User-generated Data
Information Visualization in Social Media
Multimedia Retrieval
Tagging and Games with a Purpose
Semantic Content Analysis and Indexing
Opinion Mining and Sentiment Analysis
Large-Scale Similarity Measurement, Scalability Issues and Solutions
Evaluation, Mining of Ground Truth and Data Collections
Semantic Web, Linked Data, Ontologies, Semantics and Reasoning
Novel Machine Learning Algorithms Tailored to Social Media

Important Dates

Full Paper Submission May 17, 2012
Notification of Results June 1, 2012
Camera Ready Submission t.b.a.

Workshop Committee

Organizers / Program Chairs

Program Committee

Submit Paper

Submissions will be managed by EasyChair. Please create a user account if you have not already done so, login and follow the instructions to submit a new paper.


Markus Schedl
Department of Computational Perception
Johannes Kepler University (JKU) Linz
Altenberger Str. 69, A-4040 Linz, Austria

Tel:  +43 732 2468 1512
Fax: +43 732 2468 1520
E-Mail: markus dot schedl at jku dot at

last edited by ms on 2012-05-24