Intelligent Techniques for Warehousing and Mining Sensor Network Data

Sensor network data management poses new challenges outside the scope of conventional systems where data is represented and regulated. Intelligent Techniques for Warehousing and Mining Sensor Network Data presents fundamental and theoretical issues pertaining to data management. Covering a broad range of topics on warehousing and mining sensor networks, this advanced title provides significant industry solutions to those in database, data warehousing, and data mining research communities.

Alfredo Cuzzocrea is a researcher at the Institute of High Performance Computing and Networking of the Italian National Research Council, Italy, and an adjunct professor at the Department of Electronics, Computer Science and Systems of the University of Calabria, Italy. His research interests include multidimensional data modelling and querying, data stream modelling and querying, data warehousing and OLAP, OLAM, XML data management, Web information systems modelling and engineering, knowledge representation and management models and techniques, Grid and P2P computing. He is author or co-author of more than 100 papers in referred international conferences (including EDBT, SSDBM, ISMIS, ADBIS, DEXA, DaWaK, DOLAP, IDEAS, SEKE, WISE, FQAS, SAC) and international journals (including DKE, JIIS, IJDWM, WIAS). He serves as program committee member of referred international conferences (including ICDM, SDM, PKDD, PAKDD, CIKM, ICDCS, ER, WISE, DASFAA, FQAS, SAC) and as review board member of referred international journals (including TODS, TKDE, TSMC, IS, DKE, JIIS, IPL, TPLP, COMPJ, DPDB, KAIS, INS, IJSEKE, FGCS). He also serves as PC Chair in several international conferences and as Guest Editor in international journals like JCSS, DKE, KAIS, IJBIDM, IJDMMM and JDIM.