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Researchers worldwide are currently producing more and more scholarly data of various types such as papers, books, patents, etc. Such data are big data by nature. For example, the DBLP Computer Science Bibliography provides bibliographic information on major computer science journals and proceedings. Additionally, DBLP indexes more than 2.3 million articles records containing title, pages, years and authors' information, etc. Concurrently, scholars are associated with various academic activities such as conferences, workshops, congresses, peer review, and so on. Such scenarios have motivated us to explore the Web of Scholars in the context of big scholarly data on a global scale. It is imperative and vital for researchers to drive their knowledge towards the innovative generation of values from Big Scholarly Data. The emerging worldwide Web of Scholars demands a re-evaluation of existing techniques, such as data mining, recommender systems, and social network analysis. Furthermore, there is a demand for novel ways of developing algorithms, methods and techniques to foster the analysis and interpretation of social environments such as academic collaboration networks.

In this workshop, we will explore promising areas of research in big scholarly data, with a focus on the rapidly emerging field of the Web of Scholars. This workshop also seeks to answer noteworthy research questions such as:
- How to connect scholars on the web?
- How to facilitate collaboration among scholars?
- How to find the experts in a particular field?


Researchers are welcome to submit their papers that address these questions above and other topics below which may include, but are not limited to:
- Academic social network analysis
- Scientific recommendation
- Methods and tools for analyzing big scholarly data
- Indexing, searching, and mining scholarly data
- Connecting scholars using a Web approach
- Platforms and services for the Web of Scholars
- Web tools and techniques for big scholarly data
- Paradigms to promote scientific collaboration
- Scientific trends prediction
- Applications, use cases, and evaluations of big scholarly data

Paper Submission Deadline: Jan 14, 2014 Jan 28, 2014
Author Notification: Feb 4, 2014
Final Manuscript: Feb 12, 2014



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