-------- Weitergeleitete Nachricht -------- Betreff: [AISWorld] CFP: The IJCAI-16 Workshop on Scholarly Big Data: AI Perspectives, Challenges and Ideas Datum: Tue, 12 Apr 2016 17:20:39 +0000 Von: Madian Khabsa Madian.Khabsa@microsoft.com An: aisworld@lists.aisnet.org aisworld@lists.aisnet.org
================================ Call for Workshop Papers ========================== IJCAI-16 Workshop: Scholarly Big Data: AI Perspectives, Challenges and Ideas
New York City, USA July 14 - 15, 2016 URL: http://www.cse.unt.edu/~ccaragea/ijcai2016ws.html ====================================================================================
IMPORTANT DATES --------------------------------------
Paper Submission Deadline: April 15, 2016 Author Notification: May 15, 2016 Final Manuscript due: June 6, 2016
CALL FOR PAPERS --------------------------------------
The workshop aims at bringing together researchers with diverse interdisciplinary backgrounds interested in mining, managing and searching scholarly big data using new AI technologies or analyzing their transferability from one domain to another. The topics of interest include, but are not limited to:
- Social media approaches to measuring the impact of research funding and publications as well as the impact of researchers in a particular field of study: -- Identifying influential authors, experts, and collaborators within or across disciplines. -- Modeling the referencing behavior across disciplines. -- Automatic citation recommendation. -- Modeling the referencing behavior across disciplines. - Mining large digital libraries of scientific publications and linking to other databases such as funded proposals and patents: -- Identifying research trends and topics. -- Extracting relevant information from research articles, including an article's metadata and keyphrase extraction. -- Scaling up machine learning algorithms to large research and related datasets. -- Classification and clustering of scientific trends, publications, funded proposal, patents, etc. -- Large scale linking of various entities, e.g., articles with articles by similarity, articles with their corresponding presentation slides, articles with the corresponding funded proposals. - Presenting novel datasets (e.g., based on Wikipedia, DBpedia etc.) can help researcher develop novel technologies for analyzing scientific communications - Effectively indexing and searching large scale academic documents and other resources. - Systems and case studies of academic social networks.
SUBMISSIONS --------------------------------------
Authors are invited to submit manuscripts electronically, by April 15, 2016. Submissions are to be made to EasyChair at: https://easychair.org/conferences/?conf=ijcai2016ws Each paper will be reviewed by three Program Committee members. Papers will be double-blind reviewed.
Paper format: - Papers must be written in English. - Papers must be no longer than seven pages in total: six pages for the main text of the paper (including all figures but excluding references), and one additional page for references. - Papers must be formatted according to the IJCAI guideline available at: http://ijcai-16.org/downloads/FormattingGuidelinesIJCAI-16.zip
PROGRAM COMMITTEE --------------------------------------
Xiaojun Wan, Peking University Rada Milhalcea, University of Michigan Min-Yen Kan, National University of Singapore Ani Nenkova, University of Pennsylvania Saurabh Kataria, Xerox Research Kazi Hasan, IBM Yang Peng, A*STAR, Singapore Suppawong Tuarob, Mahidol University Niket Tandon, Max-Planck-Institut für Informatik Zhaohui Wu, Pennsylvania State University Hamed Alhoori, Northern Illinois University Doina Caragea, Kansas State University Kazunari SUGIYAMA, National University of Singapore Feng Xia, Dalian University of Technology Fang Yuan, A*STAR, Singapore
WORKSHOP ORGANIZERS --------------------------------------
Cornelia Caragea, University of North Texas, USA C. Lee Giles, Pennsylvania State University, USA Sujatha Das Gollapalli, A*STAR, Singapore Madian Khabsa, Microsoft Research, USA Alex D. Wade, Microsoft Research, USA
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