Recent Collaborators


ASU/CSE Awards

Top 5% Faculty Award, Fulton Schools of Engineering, 2014
Top 5% Faculty Award, Fulton Schools of Engineering, 2012

Best Teacher Award, Fulton Schools of Engineering, 2013
Best Teacher Award, Fulton Schools of Engineering, 2013

Top 5% Faculty Award, Fulton Schools of Engineering, 2012
Top 5% Faculty Award, Fulton Schools of Engineering, 2012

Distinguished Service'09
Distinguished Service in Computer Science and Engineering Award, 2009

Researcher of the Year'08
Researcher of the Year Award,2008

Service Faculty'07
Service Faculty of the Year Award, 2007

MiNC: NSDL Middleware for Network- and Context-aware Recommendations

The mission of NSF’s National STEM Education Distributed Learning (NSDL) is to support development and coordination of educational resource collections. NSDL provides integrated access to the resulting network of learning resources through automated services. While NSDL leverages Strand maps and topic maps (such as NSDL’s TM4L) to vigorously engage the user in exploration activities, these are static and also known to place extraneous load on users. Thus, accessing internal and external resources of NSDL effectively requires a proper understanding of the personal activity context, context-aware resource discovery, and peer-network driven resource and knowledge sharing and collaborative recommendations. Current limitations of NSDL current include lack of support to select appropriate resources into a coherent learning experience and inability to leverage user’s activity context and peers in discovery.

The principal motivation for our work is to develop content personalization, preview, and collaborative recommendation services that will transform resource sharing and access to NSDL by teachers, librarians, and learners. In particular, we are developing MiNC (NSDL middleware for Network- and Context-aware Recommendations) which will provide online integrated services for

a) understanding the personal activity context through analysis of NSDL access patterns and of user’s own annotations and bookmarks,
b) context-aware resource discovery, including search, presentation, and exploration support within the knowledge structure (e.g. Strand Maps), and
c) peer discovery, peer-network management, and peer driven resource and knowledge sharing and collaborative recommendations.

MiNC will leverage the NSDL technical network services and integrate with existing Strand maps services and other related services. The middleware will provide API based services to enable future projects and other NSDL contributors to leverage MiNC components, technologies, and information spaces.

The technical impact of the work includes implementation of cutting-edge information retrieval, adaptive navigation, recommendation, and peer-networking techniques as middleware services available to NSDL users. This will require investigations into representation of the personal activity context; understanding of user’s personal context through analysis of NSDL activity patterns as well as of user documents, annotations, and bookmarks; context-aware resource discovery, including search, presentation, and exploration support, as well as context-aware summarization and previews; and peer network driven resource and knowledge sharing and recommendations and collaborative filtering techniques.

Related grant:
NSF DUE#1043583 - "MiNC: NSDL Middleware for Network- and Context-aware Recommendations (2010-2011).

NSF Project site: http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1043583

Short bio


K. Selcuk Candan is a Professor of Computer Science and Engineering at the School of Computing, Informatics, and Decision Science Engineering at the Arizona State University and is leading the EmitLab research group. He joined the department in August 1997, after receiving his Ph.D. from the Computer Science Department at the University of Maryland at College Park.


Prof. Candan's primary research interest is in the area of management of non-traditional, heterogeneous, and imprecise (such as multimedia, web, and scientific) data.  His various research projects in this domain are funded by diverse sources, including the National Science Foundation, Department of Defense, Mellon Foundation, and DES/RSA (Rehabilitation Services Administration). He has published over 140 articles and many book chapters. He has also authored 9 patents. Recently, he co-authored a book titled "Data Management for Multimedia Retrieval" for the Cambridge University Press and co-edited "New Frontiers in Information and Software as Services: Service and Application Design Challenges in the Cloud" for Springer.


Prof. Candan served an editorial board member of one of the most respected database journals, the Very Large Databases (VLDB) journal. He is currently an associate editor for the IEEE Transactions on Multimedia and the Journal of Multimedia. He has served in the organization and program committees of various conferences. In 2006, he served as an organization committee member for SIGMOD'06, the flagship database conference of the ACM and one of the best conferences in the area of management of data. In 2008, he served as a PC Chair for another leading, flagship conference of the ACM, this time focusing on multimedia research (MM'08). More recently, he served as a program committee group leader for ACM SIGMOD’10. He also served in the review board of the Proceedings of the VLDB Endowment (PVLDB). In 2011, he served in the Executive Committee of ACM SIGMM.


In 2010, he was a program co-chair for ACM CIVR'10 conference and a program group leader for ACM SIGMOD'10. In 2011, he is serving as a general co-chair for the ACM MM'11 conference. In 2012, he served as a general co-chair for ACM SIGMOD'12. In 2015, he will serve as a general co-chair for IEEE International Conference on Cloud Engineering (IC2E'15).


He is a member of the Executive Committee of ACM SIGMOD and an ACM Distinguished Scientist.


For his curriculum vitae, please click here.