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[InetBib] CFP: Joint workshop on Bibliometric-enhanced IR and NLP for Digital Libraries (BIRNDL) @JCDL2016

== Call for Papers ==
You are invited to participate in the upcoming Joint workshop on 
Bibliometric-enhanced IR and NLP for Digital Libraries (BIRNDL), to be held as 
part of the Joint Conference on Digital Libraries 2016 (JCDL 2016) in Newark, 
New Jersey, USA.


We are happy to announce that the past BIR and NLPIR4DL organizers are 
proposing this workshop at JCDL together. In conjunction with the workshop, we 
will hold the 2nd CL-SciSumm Shared Task in Scientific Document Summarization.  
Reports from the shared task systems will be featured as part of a session at 
the workshop.

=== Important Dates ===
- Submissions: 15 April 2016
- Notification: 06 May 2016
- Camera Ready Contributions: 03 June 2016
- Workshop: 23 June 2016 in Newark, New Jersey, USA

=== Aim of the Workshop ===
Current digital libraries collect and allow access to digital papers and their 
metadata (including citations), but mostly do not analyze the items they index. 
The large scale of scholarly publications poses a challenge for scholars in 
their search for relevant literature. Searchers of digital libraries, citation 
indices and journal databases are inundated with thousands of results. The 
community needs to develop techniques to better support both basic as well as 
higher-order information seeking and scholarly sensemaking activities.

The BIRNDL 2016 workshop is a joint scientific event gathering scholars from 
the BIR (Bibliometric-enhanced Information Retrieval) and the NLPIR4DL (Text 
and citation analysis for scholarly digital libraries) communities. The scope 
of BIRNDL is on scholarly publications and data - the explosion in the 
production of scientific literature and the growth of scientific enterprise; 
its consistent exponential growth approaches an empirical law. The workshop 
will investigate how natural language processing, information retrieval, 
scientometric and recommendation techniques can advance the state-of-the-art in 
scholarly document understanding, analysis and retrieval at scale. Researchers 
are in need of assistive technologies to track developments in an area, 
identify the approaches used to solve a research problem over time and 
summarize research trends. Digital libraries require semantic search, 
question-answering and automated recommendation and reviewing systems to manage 
and retrieve answers from scholarly databases. Full document text analysis can 
help to design semantic search, translation and summarization systems; citation 
and social network analyses can help digital libraries to visualize scientific 
trends, bibliometrics and relationships and influences of works and authors. 
All these approaches can be supplemented with the metadata supplied by digital 
libraries, inclusive of usage data, such as download counts.

This workshop will be relevant to scholars in the cross-disciplinary field of 
Computer Science and Digital Libraries, in particular in the research areas of 
Natural Language Processing and in Information Retrieval; it will also be 
important for all stakeholders in the publication pipeline: implementers, 
publishers and policymakers. Even when only considering the scholarly sites 
within Computer Science, we find that the field is well-represented - ACM 
Portal, IEEE Xplore, Google Scholar, PSU's CiteSeerX, MSR's Academic Search, 
Elsevier's Mendeley, Tsinghua's ArnetMiner, Trier's DBLP, Hiroshima's PRESRI; 
with this workshop we hope to bring a number of these contributors together. 
Today's publishers continue to seek new ways to be relevant to their consumers, 
in disseminating the right published works to their audience. The fact that 
formal citation metrics have become an increasingly large factor in 
decision-making by universities and funding bodies worldwide makes the need for 
research in such topics and for better methods for measuring the impact of work 
more pressing.

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

=== Workshop Topics ===
To support the previously described goals the workshop topics include (but are 
not limited to) the following:
- Information retrieval (IR) for digital libraries and scientific information 
- IR for scholarly text, e.g. citation-based IR
- IR for scientific domains, e.g. social sciences, life sciences etc.
- Information Seeking Behaviour
- Navigation, searching and browsing in scholarly DLs; Niche search in 
scholarly DLs; New information access methods for scientific papers
- Query expansion and relevance feedback approaches
- Question-answering for scholarly DLs
- Recommendations based on explicit and implicit user feedback
- Recommendation for scholarly papers, reviewers, citations and publication 
- (Social) Book Search
- Summarisation of scientific articles; Automatic creation of reviews and 
automatic qualitative assessment of submissions;
- Bibliometrics, citation analysis and network analysis for IR; Citation 
function/motivation analysis; Novel bibliographic metrics; Topical modeling 
- Knowledge discovery and analysis of the ancestry of ideas
- Metadata and controlled vocabularies for resource description and discovery; 
Automatic metadata discovery, such as language identification
- Translation, multilingual and multimedia analysis and alignment of scholarly 
- Analyses of writing style in scholarly publications
- 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
- Disambiguation issues in scholarly DLs using NLP or IR techniques; Data 
cleaning and data quality
- Classification, categorisation and clustering approaches
- Information extraction (including topic detection, entity and relation 

For the paper sessions we 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 (max. 6 pages for short and 12 pages for full papers, Springer LNCS: 
<http://www.springer.com/lncs>; exclusive of unlimited pages for references) 
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.

EasyChair: <https://easychair.org/conferences/?conf=birndl2016>

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

=== Organizers ===
Guillaume Cabanac, University of Toulouse, France
Muthu Kumar Chandrasekaran, School of Computing, National University of 
Singapore, Singapore
Ingo Frommholz, University of Bedfordshire in Luton, UK
Kokil Jaidka, Big Data Experience Lab, Adobe Research, India
Min-Yen Kan, School of Computing, National University of Singapore, Singapore
Philipp Mayr, GESIS - Leibniz Institute for the Social Sciences, Germany
Dietmar Wolfram, School of Information Studies, University of 
Wisconsin-Milwaukee, USA

=== Program Committee (TBC) ===
The below lists the committee members who have stated their support to review 
submissions to the workshop. A few have yet to be confirmed.

Akiko Aizawa, National Institute of Informatics, Japan
Iana Atanassova, Université de Franche-Comté, France
Marc Bertin, Université du Québec à Montréal, Canada
José Borbinha, INESC-ID/IST, Portugal
Colin Batchelor, Royal Society of Chemistry, Cambridge, UK
Cornelia Caragea, University of North Texas, USA
Jason S Chang, National Tsing Hua University, Taiwan
John Conroy, IDA Center for Computing Sciences
Martine De Cock, Ghent University, Belgium
Ed A. Fox, Virginia Tech, USA
Norbert Fuhr, University of Duisburg-Essen, Germany
C Lee Giles, Penn State University, USA
Bela Gipp, University of Konstanz, Germany
Nazli Goharian, Georgetown University
Sujatha Das Gollapalli, Institute for Infocomm Research, A*STAR, Singapore
Pawan Goyal, Indian Institute of Technology, Kharagpur
Björn Hammarfelt, University of Borås, Sweden
Peter Ingwersen, University of Copenhagen, Denmark
Kris Jack, Mendeley, UK
Rahul Jha, Microsoft
Noriko Kando, National Institute of Informatics, Japan
Dain Kaplan, Tokyo Institute of Technology
Roman Kern, Graz University of Technology, Austria
Claus-Peter Klas, GESIS, Germany
Marijn Koolen, University of Amsterdam, NL
Anna Korhonen, University of Cambridge, UK
Birger Larsen, Aalborg University, Denmark
John Lawrence, University of Dundee
Elizabeth Liddy, Syracuse University
Chin-Yew Lin, Microsoft Research
Xiaozhong Liu, Indiana University, Bloomington, USA
Kathy McKeown, Columbia University, USA
Stasa Milojevic, Indiana University, USA
Prasenjit Mitra, Penn State University / Qatar Computing Research Institute
Marie-Francine Moens, KU Leuven
Peter Mutschke, GESIS, Germany
Preslav Nakov, Qatar Computing Research Institute
Doug Oard, University of Maryland, College Park
Manabu Okumura, Tokyo Institute of Technology
Byung-won On, Kunsan National University
Arzucan Ozgur, Bogazici University
Cecile Paris, The Commonwealth Scientific and Industrial Research Organisation
Philipp Schaer, GESIS, Germany
Andrea Scharnhorst, DANS, NL
Henry Small, SciTech Strategies, USA
Kazunari Sugiyama, National University of Singapore
Lynda Tamine-Lechani, University Paul Sabatier, France
Simone Teufel, University of Cambridge, UK
Mike Thelwall, University of Wolverhampton, UK
Lucy Vanderwende, Microsoft Research
Vasudeva Varma, International Institute of Information Technology, Hyderabad, 
Andre Vellino, University of Toronto
Anita de Waard, Elsevier Labs
Alex Wade, Microsoft Research
Ludo Waltman, CWTS, NL
Stephen Wan, CSIRO ICT Centre
Howard D. White, Drexel University, 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@xxxxxxxxx<mailto:philipp.mayr@xxxxxxxxx>
Web: http://www.gesis.org<http://www.gesis.org/>

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