From Web To Social Web Discovering And Deploying User And Content Profiles
Download From Web To Social Web Discovering And Deploying User And Content Profiles PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get From Web To Social Web Discovering And Deploying User And Content Profiles book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
From Web to Social Web: Discovering and Deploying User and Content Profiles
Author: Bettina Berendt
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-09-17
This book constitutes the refereed proceedings of the Workshop on Web Mining, WebMine 2006, held in Berlin, Germany, September 2006. Topics included are data mining based on analysis of bloggers and tagging, web mining, XML mining and further techniques of knowledge discovery. The book is especially valuable for those interested in the aspects of Web 2.0 and its inherent dynamic and diversity of user-generated content.
Semantic Web: Ontology and Knowledge Base Enabled Tools, Services, and Applications
Semantic web continues to be an increasingly important system for allowing end-users to share and communicate information online. Semantic Web: Ontology and Knowledge Base Enabled Tools, Services and Application focuses on the information systems discipline and the tools and techniques utilized for the emerging use of semantic web. Covering topics on semantic search, ontologies, and recommendation systems, this publication is essential for academics, practitioners, and industry professionals.
Recommender Systems
Author: Dietmar Jannach
language: en
Publisher: Cambridge University Press
Release Date: 2010-09-30
In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations. This book offers an overview of approaches to developing state-of-the-art recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and content-based filtering, as well as more interactive and knowledge-based approaches. They also discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. The final chapters cover emerging topics such as recommender systems in the social web and consumer buying behavior theory. Suitable for computer science researchers and students interested in getting an overview of the field, this book will also be useful for professionals looking for the right technology to build real-world recommender systems.