Current Trends on Knowledge- Based Systems

Hernández, Giner Alor and García, Rafael Valencia, eds. (2017) Current Trends on Knowledge- Based Systems. Springer Nature, Switzerland. ISBN 978-3-319-51905-0

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Abstract

This book presents innovative and high-quality research on the implementation of conceptual frameworks, strategies, techniques, methodologies, informatics platforms and models for developing advanced knowledge-based systems and their application in different fields, including Agriculture, Education, Automotive, Electrical Industry, Business Services, Food Manufacturing, Energy Services, Medicine and others. Knowledge-based technologies employ artificial intelligence methods to heuristically address problems that cannot be solved by means of formal techniques. These technologies draw on standard and novel approaches from various disciplines within Computer Science, including Knowledge Engineering, Natural Language Processing, Decision Support Systems, Artificial Intelligence, Databases, Software Engineering, etc. As a combination of different fields of Artificial Intelligence, the area of Knowledge-Based Systems applies knowledge representation, case-based reasoning, neural networks, Semantic Web and TICs used in different domains. The book offers a valuable resource for PhD students, Master’s and undergraduate students of Information Technology (IT)-related degrees such as Computer Science, Information Systems and Electronic Engineering.

Item Type: Book
Subjects: Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Q Science > QA Mathematics > QA299.6-433 Analysis > Q334.A755 Artificial intelligence. Computational linguistics. Computer science.
Q Science > QA Mathematics > QA8.9-QA10.3 Computer science. Artificial intelligence. Computational complexity. Data structures (Computer scienc. Mathematical Logic and Formal Languages
Divisions: 03-Faculty of Engineering > 21001-Engineering Science (S3)
Depositing User: Users 1741 not found.
Date Deposited: 22 Oct 2019 08:02
Last Modified: 22 Oct 2019 08:02
URI: http://repository.unsri.ac.id/id/eprint/12463

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