Bøger af Chabane Djeraba

The conjunction of knowledge discovery and multimedia documents presents a very important challenge. This new field of knowledge discovery in multimedia documents, dealing with non-structured information such as texts, images, videos, audio and virtual data, requires the collaboration of experts in many areas of interest revolving around document management systems, data mining, visual computing, signal processing, multimedia data and machine learning. Multimedia Mining: A Highway to Intelligent Multimedia Documents will bring together experts in digital media content analysis, state-of-art data mining and knowledge discovery in multimedia database systems, knowledge engineers and domain experts from diverse applied disciplines.Multimedia documents are ubiquitous and often required, if not essential, in many applications today. This phenomenon has made multimedia documents widespread and extremely large. There are tools for managing and searching within these collections, but the need for tools to extract hidden useful knowledge embedded within multimedia objects is becoming pressing and central for many decision-making applications. The tools needed today are tools for discovering relationships between objects or segments within multimedia document components, such as classifying images based on their content, extracting patterns in sound, categorizing speech and music, and recognizing and tracking objects in video streams.Multimedia Mining: A Highway to Intelligent Multimedia Documents is designed to meet the needs of a professional audience composed of researchers and practitioners in industry and graduate-level students in computer science and engineering.

Multimedia Mining: A Highway to Intelligent Multimedia Documents brings together experts in digital media content analysis, state-of-art data mining and knowledge discovery in multimedia database systems, knowledge engineers and domain experts from diverse applied disciplines.Multimedia documents are ubiquitous and often required, if not essential, in many applications today. This phenomenon has made multimedia documents widespread and extremely large. There are tools for managing and searching within these collections, but the need for tools to extract hidden useful knowledge embedded within multimedia objects is becoming pressing and central for many decision-making applications. The tools needed today are tools for discovering relationships between objects or segments within multimedia document components, such as classifying images based on their content, extracting patterns in sound, categorizing speech and music, and recognizing and tracking objects in video streams.

Data mining essentially relies on several mathematical disciplines, many of which are presented in this second edition of this book. To motivate the reader a significant number of applications of these mathematical tools are included ranging from association rules, clustering algorithms, classification, data constraints, logical data analysis, etc.