Data Streams

Data Streams: Models and Algorithms primarily discusses issues related to the mining aspects of data streams.  Recent progress in hardware technology makes it possible for organizations to store and record large streams of transactional data. For example, even simple daily transactions such as using the credit card or phone result in automated data storage, which brings us to a fairly new topic called data streams.

This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions.

Data Streams: Models and Algorithms is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.

This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. It is intended for a professional audience, but is also appropriate for advanced-level students in computer science.

Data Streams: Models and Algorithms primarily discusses issues related to the mining aspects of data streams.  Recent progress in hardware technology makes it possible for organizations to store and record large streams of transactional data. For example, even simple daily transactions such as using the credit card or phone result in automated data storage, which brings us to a fairly new topic called data streams.

This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions.

Data Streams: Models and Algorithms is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.