Anticipatory optimization for dynamic decision making relies on a number of different scientific disciplines. On a general level, the foundations of the field may be localized at the intersection of operations research, computer science and decision theory. Closer inspection reveals the important role of branches such as simulation,...

Making Sense of Data III: A Practical Guide to Designing Interactive Data Visualizations explores a diverse range of disciplines to explain how meaning from graphical representations is extracted. Additionally,...

There is a strong need for advances in the fields of image indexing and retrieval and visual query languages for multimedia databases. Image technology is facing both classical and novel problems for the organization and filtering of increasingly large amounts of pictorial data. Novel kinds of problems, such as indexing and high-level...

Artificial Intelligence's long-term goal is to build the human level of artificial intelligence. AI was born 50 years ago, in the bumpy road has made encouraging progress, in particular, machine learning, data mining, computer vision, expert systems, natural language processing, planning, robotics and related applications have...

In the last three decades, machine learning research and practice have focused on batch learning usually using small datasets. In batch learning, the whole training data is available to the algorithm, which outputs a decision model after processing the data eventually (or most of the times) multiple times. The rationale behind this...

Since the 1960s, database systems have been playing a relevant role in the information technology field. By the mid-1960s, several systems were also available for commercial purposes. Hierarchical and network database systems provided two different perspectives and data models to organize data collections. In 1970, E. Codd wrote a...

Clustering is an important unsupervised classification technique where a set of patterns, usually vectors in multidimensional space, are grouped into clusters based on some similarity or dissimilarity criteria. In crisp clustering, each pattern is assigned to exactly one cluster, whereas in fuzzy clustering, each pattern is given a...

Data management has evolved over the years from being strictly associated with database systems, through active databases, to being a topic that has grown beyond the scope of a single field encompassing multiple aspects: distributed systems, event-driven systems, and peer-to-peer and streaming systems. The present collection of works,...

This book contains selected research results on non-traditional database systems from Japanese database research community. In traditional database research, the main emphases is how to process a large amount of fixed structured data with minimum amount of selected resources (processing time, communication overhead, memory size,...