@book {13691,
	title = {Video Mining},
	year = {2003},
	month = {2003/08/31/},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Video Mining is an essential reference for the practitioners and academicians in the fields of multimedia search engines.Half a terabyte or 9,000 hours of motion pictures are produced around the world every year. Furthermore, 3,000 television stations broadcasting for twenty-four hours a day produce eight million hours per year, amounting to 24,000 terabytes of data. Although some of the data is labeled at the time of production, an enormous portion remains unindexed. For practical access to such huge amounts of data, there is a great need to develop efficient tools for browsing and retrieving content of interest, so that producers and end users can quickly locate specific video sequences in this ocean of audio-visual data.Video Mining is important because it describes the main techniques being developed by the major players in industry and academic research to address this problem. It is the first time research from these leaders in the field developing the next-generation multimedia search engines is being described in great detail and gathered into a single volume.Video Mining will give valuable insights to all researchers and non-specialists who want to understand the principles applied by the multimedia search engines that are about to be deployed on the Internet, in studios{\textquoteright} multimedia asset management systems, and in video-on-demand systems.},
	keywords = {Computers / Client-Server Computing, Computers / Computer Science, Computers / Database Management / Data Mining, Computers / Database Management / General, Computers / Information Technology, Computers / Information Theory, Computers / Intelligence (AI) \& Semantics, Computers / Interactive \& Multimedia, Computers / Networking / General, Computers / Security / Cryptography, data mining, Data mining/ Congresses, Mathematics / General, Medical / General, multimedia systems, Multimedia systems/ Congresses, Technology \& Engineering / Electrical, Technology \& Engineering / Telecommunications},
	isbn = {9781402075490},
	author = {Rosenfeld,Azriel and David Doermann and DeMenthon,Daniel}
}
@book {15676,
	title = {Algorithm Engineering and Experiments: 4th International Workshop, Alenex 2002, San Francisco, Ca, Usa, January 4-5. 2002 : Revised Papers},
	year = {2002},
	month = {2002/09/17/},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Algorithm Engineering and Experiments, ALENEX 2002, held in San Francisico, CA, USA in January 2002.The 15 revised full papers presented were carefully reviewed and selected from 34 submissions. Among the topics addressed are hewistics for algorithms, combinatorial optimization, searching, graph computation, network optimization, scheduling, computational geometry, sorting, and clustering algorithms.},
	keywords = {Architecture / General, Artificial intelligence, Computer algorithms, Computer algorithms/ Congresses, COMPUTERS, Computers / Computer Graphics, Computers / Computer Science, Computers / Data Modeling \& Design, Computers / Data Processing, Computers / General, Computers / Programming / Algorithms, Electronic books, Mathematics / Discrete Mathematics, Medical / General},
	isbn = {9783540439776},
	author = {Mount, Dave and Stein,Clifford}
}
@book {17708,
	title = {Matrix Algorithms: Eigensystems},
	year = {2001},
	month = {2001/08/30/},
	publisher = {SIAM},
	organization = {SIAM},
	abstract = {This is the second volume in a projected five-volume survey of numerical linear algebra and matrix algorithms. It treats the numerical solution of dense and large-scale eigenvalue problems with an emphasis on algorithms and the theoretical background required to understand them. The notes and reference sections contain pointers to other methods along with historical comments. The book is divided into two parts: dense eigenproblems and large eigenproblems. The first part gives a full treatment of the widely used QR algorithm, which is then applied to the solution of generalized eigenproblems and the computation of the singular value decomposition. The second part treats Krylov sequence methods such as the Lanczos and Arnoldi algorithms and presents a new treatment of the Jacobi-Davidson method. These volumes are not intended to be encyclopedic, but provide the reader with the theoretical and practical background to read the research literature and implement or modify new algorithms.},
	keywords = {eigenvalues, Mathematics / Algebra / Linear, Mathematics / Applied, Mathematics / General, Mathematics / Mathematical Analysis, Mathematics / Matrices, Mathematics / Numerical Analysis, Matrices, Medical / General},
	isbn = {9780898715033},
	author = {Stewart, G.W.}
}
@book {15513,
	title = {Logic-Based Artificial Intelligence},
	year = {2000},
	month = {2000/12/01/},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This landmark volume represents the culmination of over 40 years of research in the use of logic as a basis for representing and manipulating problems in the field of artificial intelligence. The use of logic as a basis for commonsense reasoning was started by John McCarthy in 1959. The collection consists of both original research and surveys of almost every subject that uses logic in AI, contributed by leading scientists, and grew out of preliminary work presented at the Workshop on Logic-Based Artificial Intelligence held in Washington, DC, June 1999. All papers have been extensively refereed and revised.  The introductory article presents background on research that has transpired since 1959 and discusses the significance of each chapter in this context. The topics covered in the book are commonsense reasoning, knowledge representation, nonmonotonic reasoning, logic for causation and actions, planning and problem solving, cognitive robotics, logic for agents and actions, inductive reasoning, possibilistic logic, logic and beliefs, logic and language, computational logic, knowledge base system implementations, and applications of theorem proving and logic programming.  Logic-Based Artificial Intelligence is invaluable to graduate students and researchers in artificial intelligence, and advanced methods for database and knowledge base systems. Logic-Based Artificial Intelligence will also be of interest to those applying theorem proving methods to problems in program and hardware verification, to those who deal with large knowledge base systems, those developing cognitive robotics, and for those interested in the solution of McCarthy{\textquoteright}s 1959 "oldest planning problem in AI: getting from home to the airport".},
	keywords = {Artificial intelligence, COMPUTER LOGIC, Computers / Computer Science, Computers / Intelligence (AI) \& Semantics, Logic, Symbolic and mathematical, Mathematics / Logic, Medical / General},
	isbn = {9780792372240},
	author = {Minker, Jack}
}
