You are invited to participate in the upcoming 5th workshop on Bibliometric-enhanced Information Retrieval (BIR), to be held as part of the 39th European Conference on Information Retrieval (ECIR). http://ecir2017.org/

• Workshop proceedings are available http://ceur-ws.org/Vol-1823/
• Authors of accepted papers will be invited to submit extended versions to a Special Issue on “Bibliometric-enhanced IR” to be published in the journal Scientometrics.
• Please be aware of the fact that at least one author per paper needs to register (one-day workshop at £ 180) for the workshop and attend the workshop to present the work.
• Workshop is in Sir Ian Wood building, Robert Gordon University (RGU), Room: N344

Agenda

• Abstracts: 31 January 2017
• Submissions: 12 February 2017 (extended)
• Notification: 03 March 2017
• Camera Ready Contributions: 24 March 2017
• Workshop: 09 April 2017 in Aberdeen, Scotland UK

Bibliometric techniques are not yet widely used to enhance retrieval processes in search systems, although they offer value-added effects for users. In this workshop we will explore how statistical modelling of scholarship, such as Bradfordizing or network analysis of coauthorship network, or simple citation graphs, can improve retrieval services for specific communities, as well as for large, cross-domain collections like Mendeley. This workshop aims to raise awareness of the missing link between Information Retrieval (IR) and bibliometrics/scientometrics and to create a common ground for the incorporation of bibliometric-enhanced services into retrieval at the scholarly search engine interface.

See proceedings of the former BIR workshops at ECIR 2014 <http://ceur-ws.org/Vol-1143/>, ECIR 2015 <http://ceur-ws.org/Vol-1344/>, ECIR 2016 <http://ceur-ws.org/Vol-1567/>, JCDL 2016 <http://ceur-ws.org/Vol-1610/>.

In this 5th 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. Bibliometric techniques are not yet widely used to enhance retrieval processes, yet they offer value-added effects for users. Our interests include information retrieval, information seeking, science modelling, network analysis, and natural language processing. 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 search systems 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, natural language processing, digital libraries, and approaches to visualize search and retrieval to move toward a deeper understanding of this research challenge.

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

• Recommendation for scholarly papers, reviewers, citations and  publication venues 

• (Social) Book Search

• Information extraction (including topic detection, entity and relation extraction)

We especially invite descriptions of running projects and ongoing work. Papers that investigate multiple themes directly are especially welcome.

This workshop is also informed by an ongoing COST Action TD1210 KnowEscape.

• Iana Atanassova, Centre Tesnière, Université de Franche-Comté, France

• Joeran Beel, Trinity College Dublin, Ireland

• Patrice Bellot, Aix-Marseille Université - CNRS (LSIS), France

• Marc Bertin, Université du Québec à Montréal, Canada

• Jose Borbinha, IST / INESC-ID, Portugal

• Cornelia Caragea, University of North Texas, USA

• Zeljko Carevic, GESIS - Leibniz Institute for the Social Sciences, Germany

• Muthu Kumar Chandrasekaran, National University of Singapore, Singapore

• Edward Fox, Virginia Polytechnic Institute and State University, USA

• Gilles Hubert, University of Toulouse, France

• Kokil Jaidka, University of Pennsylvania, USA

• Petr Knoth, The Open University, UK

• Marijn Koolen, Huygens Institute for the History of the Netherlands, Netherlands

• Cyril Labbé, Grenoble University, France

• Vincent Larivière, EBSI-UdeM, Canada

• Birger Larsen, Aalborg University Copenhagen, Denmark

• Stasa Milojevic, Indiana University, USA

• Peter Mutschke, GESIS – Leibniz Institute for the Social Sciences, Germany

• Philipp Schaer, TH Cologne, Germany

• Vivek Singh, Banaras Hindu University, India

• Cassidy Sugimoto, Indiana University Bloomington, USA

• Lynda Tamine, University of Toulouse, France

• Ludovic Tanguy, University of Toulouse, France

• Dietmar Wolfram, University of Wisconsin-Milwaukee, USA

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