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Speaking in Images offers an engaging and rare collection of interviews with the directors who have changed the face of Chinese and international cinema. Michael Berry's discussions with such directors as Ang Lee (Crouching Tiger, Hidden Dragon), Zhang Yimou (Hero), Chen Kaige (Farewell My Concubine), Stanley Kwan...

Speaking in Images offers an engaging and rare collection of interviews with the directors who have changed the face of Chinese and international cinema. Michael Berry's discussions with such directors as Ang Lee (Crouching Tiger, Hidden Dragon), Zhang Yimou (Hero), Chen Kaige (Farewell My Concubine), Stanley Kwan...

Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory.

As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be...

Michael Berry takes an innovative look at the representation of six specific historical traumas in modern...

This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a comprehensive reference to the field. The book is organized into eight chapters that cover the following topics: discretization, feature extraction and selection, classification, clustering, topic modeling, graph analysis and applications. Practitioners and graduate students can use the volume as an...

Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory.

As the volume of digitized textual media continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be...