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Wei Emma Zhang; Quan Z. Sheng978-3-319-94935-22018 Edition 1- This book incorporates an extensive survey that overviews the main techniques and research works for the knowledge extraction and querying in knowledge bases. Two types of knowledge bases are introduced, discussed and compared. Based on the survey, key challenges of the addressed topics are discussed. A framework for data management in knowledge base are proposed and for each component in this framework, we provide description and discussion. Thus, this book can be a good reference for the readers who seek to have an overview of knowledge base data management.
- This book covers several important research topics that are under the umbrella of querying knowledge base and knowledge extraction for the construction of knowledge base. The authors discuss the problems and provide solutions for speeding up querying process, predicting query performance, knowledge cleaning, knowledge clustering and constructing knowledge base from unstructured data. For each problem, this book provides not only technical solutions, but also design and implementation details. Therefore, this book provides both theoretical and applied computing scientific research, making it attractive to a variety set of readers from both academia and industry.
- The book provides extensive analysis and evaluations from the real-world datasets including knowledge base queries and knowledge data obtained from different sources. Analysis results from the performance study draws a number of open research issues for knowledge extraction and querying. These open research issues and future directions are beneficial for those adopting knowledge base techniques
€180 €16210% OFF