Ebook: Multimedia Services in Intelligent Environments: Advances in Recommender Systems

Multimedia services are now commonly used in various activities in the daily lives of humans. Related application areas include services that allow access to large depositories of information, digital libraries, e-learning and e-education, e-government and e-governance, e-commerce and e-auctions, e-entertainment, e-health and e-medicine, and e-legal services, as well as their mobile counterparts (i.e., m-services). Despite the tremendous growth of multimedia services over the recent years, there is an increasing demand for their further development. This demand is driven by the ever-increasing desire of society for easy accessibility to information in friendly, personalized and adaptive environments.

In this book at hand, we examine recent Advances in Recommender Systems. Recommender systems are crucial in multimedia services, as they aim at protecting the service users from information overload. The book includes nine chapters, which present various recent research results in recommender systems.

This research book is directed to professors, researchers, application engineers and students of all disciplines who are interested in learning more about recommender systems, advancing the corresponding state of the art and developing recommender systems for specific applications.

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Multimedia services are now commonly used in various activities in the daily lives of humans. Related application areas include services that allow access to large depositories of information, digital libraries, e-learning and e-education, e-government and e-governance, e-commerce and e-auctions, e-entertainment, e-health and e-medicine, and e-legal services, as well as their mobile counterparts (i.e., m-services). Despite the tremendous growth of multimedia services over the recent years, there is an increasing demand for their further development. This demand is driven by the ever-increasing desire of society for easy accessibility to information in friendly, personalized and adaptive environments.

In this book at hand, we examine recent Advances in Recommender Systems. Recommender systems are crucial in multimedia services, as they aim at protecting the service users from information overload. The book includes nine chapters, which present various recent research results in recommender systems.

This research book is directed to professors, researchers, application engineers and students of all disciplines who are interested in learning more about recommender systems, advancing the corresponding state of the art and developing recommender systems for specific applications.

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Multimedia services are now commonly used in various activities in the daily lives of humans. Related application areas include services that allow access to large depositories of information, digital libraries, e-learning and e-education, e-government and e-governance, e-commerce and e-auctions, e-entertainment, e-health and e-medicine, and e-legal services, as well as their mobile counterparts (i.e., m-services). Despite the tremendous growth of multimedia services over the recent years, there is an increasing demand for their further development. This demand is driven by the ever-increasing desire of society for easy accessibility to information in friendly, personalized and adaptive environments.

In this book at hand, we examine recent Advances in Recommender Systems. Recommender systems are crucial in multimedia services, as they aim at protecting the service users from information overload. The book includes nine chapters, which present various recent research results in recommender systems.

This research book is directed to professors, researchers, application engineers and students of all disciplines who are interested in learning more about recommender systems, advancing the corresponding state of the art and developing recommender systems for specific applications.

Content:
Front Matter....Pages i-x
Multimedia Services in Intelligent Environments: Advances in Recommender Systems....Pages 1-5
A Survey of Approaches to Designing Recommender Systems....Pages 7-30
Hybrid User Model for Capturing a User’s Information Seeking Intent....Pages 31-63
Recommender Systems: Network Approaches....Pages 65-79
Toward the Next Generation of Recommender Systems: Applications and Research Challenges....Pages 81-98
Content-Based Recommendation for Stacked-Graph Navigation....Pages 99-113
Pattern Extraction from Graphs and Beyond....Pages 115-145
Dominant AHP as Measuring Method of Service Values....Pages 147-161
Applications of a Stochastic Model in Supporting Intelligent Multimedia Systems and Educational Processes....Pages 163-174

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Multimedia services are now commonly used in various activities in the daily lives of humans. Related application areas include services that allow access to large depositories of information, digital libraries, e-learning and e-education, e-government and e-governance, e-commerce and e-auctions, e-entertainment, e-health and e-medicine, and e-legal services, as well as their mobile counterparts (i.e., m-services). Despite the tremendous growth of multimedia services over the recent years, there is an increasing demand for their further development. This demand is driven by the ever-increasing desire of society for easy accessibility to information in friendly, personalized and adaptive environments.

In this book at hand, we examine recent Advances in Recommender Systems. Recommender systems are crucial in multimedia services, as they aim at protecting the service users from information overload. The book includes nine chapters, which present various recent research results in recommender systems.

This research book is directed to professors, researchers, application engineers and students of all disciplines who are interested in learning more about recommender systems, advancing the corresponding state of the art and developing recommender systems for specific applications.

Content:
Front Matter....Pages i-x
Multimedia Services in Intelligent Environments: Advances in Recommender Systems....Pages 1-5
A Survey of Approaches to Designing Recommender Systems....Pages 7-30
Hybrid User Model for Capturing a User’s Information Seeking Intent....Pages 31-63
Recommender Systems: Network Approaches....Pages 65-79
Toward the Next Generation of Recommender Systems: Applications and Research Challenges....Pages 81-98
Content-Based Recommendation for Stacked-Graph Navigation....Pages 99-113
Pattern Extraction from Graphs and Beyond....Pages 115-145
Dominant AHP as Measuring Method of Service Values....Pages 147-161
Applications of a Stochastic Model in Supporting Intelligent Multimedia Systems and Educational Processes....Pages 163-174
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