Table of contents
About this book
This must-read text/reference presents an overview of smart information systems for both the private and public sector, highlighting the research questions that can be studied by applying computational intelligence.
The book demonstrates how to transform raw data into effective smart information services, covering the challenges and potential of this approach. Each chapter describes the algorithms, tools, measures and evaluations used to answer important questions. This is then further illustrated by a diverse selection of case studies reflecting genuine problems faced by SMEs, multinational manufacturers, service companies, and the public sector.
Topics and features:
- Provides a state-of-the-art introduction to the field, integrating contributions from both academia and industry
- Includes numerous individual use cases, which outline the need for smart information systems that help in typical situations faced by many on a daily basis
- Reviews novel information aggregation services that illustrate how textual data can be employed to generate smart information services
- Discusses personalization and recommendation systems that tailor information based on users’ individual preferences
- Examines sensor-based knowledge acquisition services, describing how the analysis of sensor data can be used to provide a clear picture of our world
Offering practical and accessible guidance for the application of computational intelligence to solving real-world problems, this volume will prove invaluable to researchers and professionals involved in information retrieval, machine learning and data analysis.
Dr. Frank Hopfgartner is Director of the Competence Center Information Retrieval and Machine Learning of the Distributed Artificial Intelligence Laboratory, and lecturer at the Berlin Institute of Technology, Berlin, Germany.
Editors and affiliations
- DOI https://doi.org/10.1007/978-3-319-14178-7
- Copyright Information Springer International Publishing Switzerland 2015
- Publisher Name Springer, Cham
- eBook Packages Computer Science
- Print ISBN 978-3-319-14177-0
- Online ISBN 978-3-319-14178-7
- Series Print ISSN 2191-6586
- Series Online ISSN 2191-6594
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