Workshop on Recommender Systems and Big Data Analytics (RS-BDA'16)

co-located with i-KNOW 2016
(Tuesday, 18.10.2016)

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Submission deadline (extended!): August 25, 2016 CEST

Objectives

Recommender systems are acknowledged as an essential instrument to support users in finding relevant information in an overloaded information space. While they have been proven successful in e.g., e-commerce applications, they can also support organizations in better identifying competences, help engage users in a continuous and dynamic knowledge exchange, and customize dissemination of knowledge as much as possible. Moreover, the advent of the big data era has posed the need for high scalability and real-time processing of frequent data updates, and thus, has brought new challenges for the recommender systems’ research community. The objective of this workshop is to bring together researchers and practitioners involved in developing, testing, and maintaining (social) recommender systems, especially in the light of big data. The workshop focuses on all aspects of recommender systems and big data analytics and it will provide a forum for discussing current practices and recent research results. RS-BDA'16 is co-located with i-KNOW 2016 (http://i-know.tugraz.at/).

Program (Tuesday, 18.10.2016 / Room 8)

  • 10:30 – 10:50: Welcome to Session 1 by Dominik Kowald

  • 10:55 – 11:25: Long paper
    Mohsen Shahriari, Sabrina Haefele and Ralf Klamma
    Contextualized versus Structural Overlapping Communities in Social Media
    (paper) (slides)

  • 11:30 – 11:50: Short paper
    Thi Ngoc Trang Tran, Muesluem Atas, Martin Stettinger and Alexander Felfernig
    An extension of CHOICLA User Interfaces for Configurable Products
    (paper) (slides)

  • 11:55 – 12:15: Short paper
    Matthias Traub, Emanuel Lacic, Dominik Kowald, Martin Khar and Elisabeth Lex
    Need Help? Recommending Social Care Institutions
    (paper) (slides)

  • 12:20 – 12:30: Closing of Session 1 by Dominik Kowald

  • 12:30 – 14:00: Lunch break

  • 14:00 – 14:10: Welcome to Session 2 by Emanuel Lacic

  • 14:15 – 14:45: Long paper
    Pawel Matuszyk, Rene Tatua Castillo, Daniel Kottke and Myra Spiliopoulou
    A Comparative Study on Hyperparameter Optimization for Recommender Systems
    (paper) (slides)

  • 14:50 – 15:20: Long paper
    Rebekka Alm and Bodo Urban
    Facilitating information exchange in assembly assistance by recommending contextualized annotations
    (paper) (slides)

  • 15:25 – 15:45: Short paper
    Mohsen Shahriari, Ying Li and Ralf Klamma
    Analysis of Overlapping Communities in Signed Complex Networks
    (paper) (slides)

  • 15:50 – 16:00: Closing of Session 2 by Emanuel Lacic

Authors of long papers have 20 minutes dedicated for presenting their work and 10 minutes for discussion. Short papers are supposed to be presented in 15 minutes with 5 minutes allocated for discussion.

Call for Papers

The main topic of this workshop is the broad research area of recommender systems and how it is connected with big data analytics. Thus, it is our main intention to bring together researchers and practitioners in these areas to discuss novel trends in analyzing big data for recommender systems. This workshop theme should be of great interest for i-KNOW 2016 attendees since both recommender systems and big data analytics are important research instruments at the intersection of the disciplines of knowledge discovery, Web & data science as well as social computing.

Overall topics to be adressed by this workshop include but are not limited to:

  • Personalization and recommendations in data-intensive environments
  • New trends and methods in big data analytics
  • Big data analytics for recommender systems
  • Novel recommender algorithms
  • Roles & Rights in recommender systems
  • Federated recommender systems
  • Case studies of real-world implementations
  • Evaluation methodologies
  • Serendipity & diversity in recommender systems
  • Recommendations for long tail content
  • Field and user studies
  • Context-aware systems
  • Cognitive aspects in recommender systems
  • Large, unstructured and social data for recommendations
  • Big data and privacy issues
  • Data Management and Data Integration
  • Scalable and Distributed Architectures
  • Recommendations in TEL
  • Trust and reputation in recommender systems
  • User interfaces for recommender systems
  • Cross-domain recommender systems
  • (Near) Real-time methods

Within these topics, we encourage short research papers (2 - 4 pages) and long research papers (6 - 8 pages), both in ACM double-column conference paper style. All submitted papers must:

All papers will be peer-reviewed and must not be under review in any other conference, workshop or journal. Accepted papers will be published in CEUR (http://ceur-ws.org/) and best papers will be published in ACM Digitial Library (http://dl.acm.org/)

In order to support the scientific community we offer reduced prices to workshop participants: 480 euro for the full 2 day conference. This is not visible on the i-KNOW website. Workshop participants will receive a promotion code for the reduced pricing.

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Venue

RS-BDA'16 is co-located with i-KNOW 2016 (http://i-know.tugraz.at/)

Location:
Messe Congress Graz
Messeplatz 1
8010 Graz
Austria

Important Dates

  • Deadline (extended!): July August 25, 2016
  • Accept/Reject Notification: September 05, 2016
  • Camera ready version: September 16, 2016
  • Early-bird registration: September 20, 2016
  • i-KNOW 2016: October 18-19, 2016

Official Hashtag

#rsbda

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