Название: Managing Data From Knowledge Bases: Querying and Extraction Автор: Wei Emma Zhang, Quan Z. Sheng
Издательство: Springer
ISBN: 3319949349
Год: 2018
Страниц: 148
Язык: английский
Формат: pdf (true), epub
Размер: 13,9 MB
Knowledge bases (KBs) are the most essential components in realizing semantic computing for better human-machine interaction experiences. Knowledge bases supply facts and relationships for use in computation by machines. This can facilitate artificial intelligence (AI) tools with the ability to reason and explain. Over the years, knowledge base has been receiving much attention, both from academia and industry, as a resource for providing knowledge, an auxiliary tool for facilitating the searching on search engines, and an expert system for helping in decision making.
Knowledge available for improving computations by AI tools has grown to become quite large, which presents a number of technical challenges including efficient knowledge retrieval and automatic knowledge base construction. Among the books on the market that cover various challenges related to KBs, this book presents one of the rare attempts to present innovative solutions for the knowledge extraction and querying in knowledge bases.
These topics are under the umbrella of extracting knowledge from unstructured data for the effective construction of knowledge bases and querying knowledge bases based on a learning-based cache framework. The book overviews key findings from the authors’ intensive research experience in analyzing data from different knowledge sources for knowledge base queries and knowledge base construction. The extensive references included in this book will help the interested readers find out more information on the discussed topics.
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