[Sigmetrics] [BIR at ECIR] CfP 7th Bibliometric-enhanced Information Retrieval workshop at ECIR 2018

Guillaume Cabanac guillaume.cabanac at univ-tlse3.fr
Mon Nov 6 04:27:10 EST 2017

== First Call for Papers ==
You are invited to participate in the upcoming 7th international workshop on Bibliometric-enhanced Information Retrieval (BIR 2018), to be held as part of the 40th European Conference on Information Retrieval (ECIR 2018). 


=== Important Dates ===
- Submissions: 15 January 2018
- Notifications: 15 February 2018
- Camera Ready Contributions: 15 March 2018
- Workshop: 26 March 2018 in Grenoble, France

=== Aim of the Workshop ===
In this 7th 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. 
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/>, ECIR 2017 <http://ceur-ws.org/Vol-1823/>, JCDL 2016 <http://ceur-ws.org/Vol-1610/> and SIGIR 2017 <http://ceur-ws.org/Vol-1888/>.

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.

=== 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
- 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 as well as contributions from industry. Papers that investigate multiple themes directly are especially welcome.

=== Submission Details ===
All submissions must be written in English following Springer LNCS author guidelines (6 to 12 pages) and should be submitted as PDF files to EasyChair. All submissions will be reviewed by at least two independent reviewers. Please be aware of the fact that at least one author per paper needs to register for the workshop and attend the workshop to present the work. In case of no-show the paper (even if accepted) will be deleted from the proceedings AND from the program.

Springer LNCS: <http://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines>  
EasyChair: <https://easychair.org/conferences/?conf=bir2018>  

Workshop proceedings will be deposited online in the CEUR workshop proceedings publication service (ISSN 1613-0073) - This way the proceedings will be permanently available and citable (digital persistent identifiers and long term preservation).

Program Committee (under constitution)

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

Cfp on Twitter <https://twitter.com/gcabanac/status/926899604133695494>, please retweet!

Guillaume Cabanac, PhD

University of Toulouse, France
Computer Science Department

“If you find something interesting
 drop everything else and pursue it!” – B.F. Skinner

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