[Sigmetrics] Program of the 3rd Workshop on Bibliometric-enhanced Information Retrieval @ECIR2016 published

[Mayr-Schlegel, Philipp]

== Workshop program published ==
You are invited to participate in the upcoming 3rd international workshop on Bibliometric-enhanced Information Retrieval (BIR 2016), to be held as part of the 38th European Conference on Information Retrieval (ECIR).

The program of the full day workshop can be found here:
<http://www.gesis.org/en/events/events-archive/conferences/ecirworkshop2016/>

We are happy to announce that Marijn Koolen (University of Amsterdam, NL) will give a keynote "Bibliometrics in Online Book Discussions: Lessons for Complex Search Tasks" at the workshop.

=== Important Dates ===
- Workshop: 20 March 2016 in Padova, Italy

=== Aim of the Workshop ===
In this third workshop we aim to engage with the IR community about possible links to bibliometrics and complex network theory which also explores networks of scholarly communication (see papers and presentations of the first workshop <http://www.gesis.org/en/events/events-archive/conferences/ecirworkshop2014/> and second workshop <http://www.gesis.org/en/events/events-archive/conferences/ecirworkshop2015/>). Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, yet they offer value-added effects for users. Our interests include information retrieval, information seeking, science modelling, network analysis, and digital libraries. The goal is to apply insights from bibliometrics, scientometrics, and informetrics to concrete practical problems of information retrieval and browsing.

Retrieval evaluations have shown that simple text-based retrieval methods scale up well but do not progress. Traditional retrieval has reached a high level in terms of measures like precision and recall, but scientists and scholars still face challenges present since the early days of digital libraries: mismatches between search terms and indexing terms, overload from result sets that are too large and complex, and the drawbacks of text-based relevance rankings. Therefore we will focus on statistical modelling and corresponding visualizations of the evolving science system. Such analyses have revealed not only the fundamental laws of Bradford and Lotka, but also network structures and dynamic mechanisms in scientific production. Statistical models of scholarly activities are increasingly used to evaluate specialties, to forecast and discover research trends, and to shape science policy. Their use as tools in navigating scientific information in public digital libraries is a promising but still relatively new development. We will explore how statistical modelling of scholarship can improve retrieval services for specific communities, as well as for large, cross-domain collections. Some of these techniques are already used in working systems but not well integrated in larger scholarly IR environments.
The availability of new IR test collections that contain citation and bibliographic information like the iSearch collection or the ACL collection could deliver enough ground to interest (again) the IR community in these kind of bibliographic systems. The long-term research goal is to develop and evaluate new approaches based on informetrics and bibliometrics.

The aim of this workshop is to bring together researchers and practitioners from different domains, such as information retrieval, information seeking, science modelling, bibliometrics, scientometrics, network analysis, digital libraries, and approaches to visualize search and retrieval to move toward a deeper understanding of this research challenge.

This workshop is also informed by an ongoing COST Action TD1210 KnowEscape. http://www.knowescape.org

=== Workshop Topics ===
To support the previously described goals the workshop topics include (but are not limited to) the following:
- IR for digital libraries and scientific information portals
- IR for scientific domains, e.g. social sciences, life sciences etc.
- Information Seeking Behaviour
- Bibliometrics, citation analysis and network analysis for IR
- Query expansion and relevance feedback approaches
- Science Modelling (both formal and empirical)
- Task based user modelling, interaction, and personalisation
- (Long-term) Evaluation methods and test collection design
- Collaborative information handling and information sharing
- Classification, categorisation and clustering approaches
- Information extraction (including topic detection, entity and relation extraction)
- Recommendations based on explicit and implicit user feedback
- (Social) Book Search

=== Organizers ===
Philipp Mayr, GESIS - Leibniz Institute for the Social Sciences, Germany
Ingo Frommholz, University of Bedfordshire in Luton, UK
Guillaume Cabanac, University of Toulouse, France


=== Program Committee ===
Iana Atanassova, Université de Franche-Comté (France)
Marc Bertin, Université du Québec à Montréal (Canada)
José Borbinha, INESC-ID/IST (Portugal)
Cornelia Caragea, University of North Texas (USA)
Martine De Cock, Ghent University (Belgium)
Ed A. Fox, Virginia Tech (USA)
Norbert Fuhr, University of Duisburg-Essen (Germany)
Björn Hammarfelt, University of Borås (Sweden)
Peter Ingwersen, University of Copenhagen (Denmark)
C. Lee Giles, Pennsylvania State University (USA)
Birger Larsen, Aalborg University (Denmark)
Claus-Peter Klas, GESIS (Germany)
Marijn Koolen, University of Amsterdam (NL)
Kris Jack, Mendeley (UK)
Stasa Milojevic, Indiana University (USA)
Peter Mutschke, GESIS  (Germany)
Philipp Schaer, GESIS (Germany)
Henry Small, SciTech Strategies (USA)
Lynda Tamine-Lechani, University Paul Sabatier (France)
Simone Teufel, University of Cambridge (UK)
Howard D. White, Drexel University (USA)
Ludo Waltman, CWTS (NL)
Dietmar Wolfram, University of Wisconsin (USA)

--
Dr. Philipp Mayr
Team Leader

GESIS - Leibniz Institute for the Social Sciences
Unter Sachsenhausen 6-8,  D-50667 Köln, Germany
Tel: + 49 (0) 221 / 476 94 -533
Email: philipp.mayr at gesis.org<mailto:philipp.mayr at gesis.org>
Web: http://www.gesis.org<http://www.gesis.org/>

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