Table of contents
About this book
This book introduces a novel type of expert finder system that can determine the knowledge that specific users within a community hold, using explicit and implicit data sources to do so. Further, it details how this is accomplished by combining granular computing, natural language processing and a set of metrics that it introduces to measure and compare candidates’ suitability. The book describes profiling techniques that can be used to assess knowledge requirements on the basis of a given problem statement or question, so as to ensure that only the most suitable candidates are recommended.
The book brings together findings from natural language processing, artificial intelligence and big data, which it subsequently applies to the context of expert finder systems. Accordingly, it will appeal to researchers, developers and innovators alike.
Granular computing Knowledge representation Concept mining Knowledge visualization Knowledge profiling and modeling Knowledge analytics Machine learning NLP Neuro linguistig programming Big data analytics
- DOI https://doi.org/10.1007/978-3-030-22978-8
- Copyright Information Springer Nature Switzerland AG 2019
- Publisher Name Springer, Cham
- eBook Packages Business and Management
- Print ISBN 978-3-030-22977-1
- Online ISBN 978-3-030-22978-8
- Series Print ISSN 2196-4130
- Series Online ISSN 2196-4149
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