Verwandte Artikel zu Searching Multimedia Databases by Content (Advances...

Searching Multimedia Databases by Content (Advances in Database Systems, 3, Band 3) - Hardcover

Buch 40 von 42: Advances in Database Systems

Faloutsos, Christos

 
9780792397779: Searching Multimedia Databases by Content (Advances in Database Systems, 3, Band 3)

Inhaltsangabe

Searching Multimedia Databases by Content bridges the gap between the database and signal processing communities by providing the necessary background information for the reader and presenting it along with the intuition and mechanics of the best existing tools in each area.
The first half of Searching Multimedia Databases by Content reviews the most successful database access methods, in increasing complexity, reaching up to spatial access methods and text retrieval. In all cases, the emphasis is on practical approaches that have been incorporated in commercial systems, or that seem very promising.
The second half of the book uses the above access methods to achieve fast searching in a database of signals. A general methodology is presented, which suggests extracting a few good features from each multimedia object, thus mapping objects into points in a metric space. Finally, the book concludes by presenting some recent successful applications of the methodology on time series and color images.
Searching Multimedia Databases by Content is targeted towards researchers and developers of multimedia systems. The book can also serve as a textbook for a graduate course on multimedia searching, covering both access methods as well as the basics of signal processing.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

Danai Koutra is an Assistant Professor in Computer Science and Engineering at University of Michigan, Ann Arbor. Her research interests include large-scale graph mining, graph similarity and matching, graph summarization, and anomaly detection. DanaiâEUR(TM)s research has been applied mainly to social, collaboration, and web networks, as well as brain connectivity graphs. She holds one ""rate-1"" patent and has six (pending) patents on bipartite graph alignment. Danai won the 2016 ACM SIGKDD Dissertation award, and an honorable mention for the SCS Doctoral Dissertation Award (CMU). She has multiple papers in top data mining conferences, including two award-winning papers, she has given three tutorials, and her work has been covered by the popular press, such as the MIT Technology Review. She has worked at IBM Watson, Microsoft Research, and Technicolor. She earned her Ph.D. and M.S. in Computer Science from CMU in 2015 and her diploma in Electrical and Computer Engineering at the National Technical University of Athens in 2010.Christos Faloutsos is a Professor at Carnegie Mellon University. He has received the Presidential Young Investigator Award by the National Science Foundation (1989), the Research Contributions Award in ICDM 2006, the SIGKDD Innovations Award (2010), 24 ""best paper"" awards (including 5 ""test of time"" awards), and 4 teaching awards. Six of his advisees have attracted KDD or SCS dissertation awards, He is an ACM Fellow, he has served as a member of the executive committee of SIGKDD; he has published over 350 refereed articles, 17 book chapters, and 2 monographs. He holds seven patents (and 2 pending), and he has given over 40 tutorials and over 20 invited distinguished lectures. His research interests include large-scale data mining with emphasis on graphs and time sequences; anomaly detection, tensors, and fractals.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.