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[InetBib] CfP: 7th Int. Workshop on Bibliometric-enhanced Information Retrieval @ECIR2018

== 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 

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 
- Recommendations based on explicit and implicit user feedback
- Recommendation for scholarly papers, reviewers, citations and  publication 
- (Social) Book Search
- Information extraction (including topic detection, entity and relation 

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 

Springer LNCS: 

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 

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

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

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@xxxxxxxxx<mailto:philipp.mayr@xxxxxxxxx>
Web: http://www.gesis.org<http://www.gesis.org/>

Listeninformationen unter http://www.inetbib.de.