Advanced Techniques in Web Intelligence-2

Web User Browsing Behaviour and Preference Analysis

AvJuan D. Velásquez,Vasile Palade

Häftad, Engelska, 2014

Del 452 i serien Studies in Computational Intelligence

1 114 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

This research volume focuses on analyzing the web user browsing behaviour and preferences in traditional web-based environments, social networks and web 2.0 applications, by using advanced techniques in data acquisition, data processing, pattern extraction and cognitive science for modeling the human actions. The book is directed to graduate students, researchers/scientists and engineers interested in updating their knowledge with the recent trends in web user analysis, for developing the next generation of web-based systems and applications.

Produktinformation

Utgivningsdatum:2014-10-15
Mått:155 x 235 x 12 mm
Vikt:312 g
Format:Häftad
Språk:Engelska
Serie:Studies in Computational Intelligence
Antal sidor:184
Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN:9783642430350

Utforska kategorier

Artificiell intelligens inom Data och IT

Recensioner i media

From the reviews: "This volume presents a progression of ideas, starting with data gathering, extending through behavioral characterization and user modeling, and ending with applications. Extensive references to the research literature accompany each chapter, and a rather brief subject index concludes the volume. This book is suitable for researchers and graduate students looking for a survey of current trends in the modeling of web user behavior from the perspective of web data analysis or cognitive science." (R. M. Malyankar, ACM Computing Reviews, February, 2013)

Innehållsförteckning

New Trends in Web User Behaviour Analysis.- Web Usage Data Pre-processing.- Cognitive Science forWeb Usage Analysis.- Web Usage Mining: Discovering Usage Patterns for Web Applications.- Web Opinion Mining and Sentimental Analysis.- Web Usage Based Adaptive Systems.- Recommender Systems: Sources of Knowledge and Evaluation Metrics.