Knowledge based + database = intelligent systems

Author(s):  
A. P. Ablong
Author(s):  
Paul Smart

AbstractThe World Wide Web has had a notable impact on a variety of epistemically relevant activities, many of which lie at the heart of the discipline of knowledge engineering. Systems like Wikipedia, for example, have altered our views regarding the acquisition of knowledge, while citizen science systems such as Galaxy Zoo have arguably transformed our approach to knowledge discovery. Other Web-based systems have highlighted the ways in which the human social environment can be used to support the development of intelligent systems, either by contributing to the provision of epistemic resources or by helping to shape the profile of machine learning. In the present paper, such systems are referred to asknowledge machines. In addition to providing an overview of the knowledge machine concept, the present paper reviews a number of issues that are associated with the scientific and philosophical study of knowledge machines. These include the potential impact of knowledge machines for the theory and practice of knowledge engineering, the role of social participation in the realization of knowledge-based processes, and the role of standardized, semantically enriched data formats in supporting thead hocassembly of special-purpose knowledge systems and knowledge processing pipelines.


Author(s):  
Zhaohao Sun ◽  
Jun Han ◽  
Dong Dong ◽  
Shuliang Zhao

Trust is significant for sustainable development of e-commerce and has received increasing attention in e-commerce, multiagent systems (MAS), and artificial intelligence (AI). However, little attention has been given to the theoretical foundation and intelligent techniques for trust in e-commerce from a viewpoint of intelligent systems and engineering. This chapter will fill this gap by examining engineering of experience-based trust in e-commerce from the viewpoint of intelligent systems. It looks at knowledgebased trust, inference-based trust and their interrelationships with experience-based trust. It also examines scalable trust in e-commerce. It proposes a knowledge based model of trust in e-commerce and a system architecture for METSE: a multiagent system for experience-based trust in e-commerce. The proposed approach in this chapter will facilitate research and development of trust, multiagent systems, e-commerce and e-services.


2019 ◽  
Vol 1 (4) ◽  
pp. 333-349 ◽  
Author(s):  
Peilu Wang ◽  
Hao Jiang ◽  
Jingfang Xu ◽  
Qi Zhang

Knowledge graph (KG) has played an important role in enhancing the performance of many intelligent systems. In this paper, we introduce the solution of building a large-scale multi-source knowledge graph from scratch in Sogou Inc., including its architecture, technical implementation and applications. Unlike previous works that build knowledge graph with graph databases, we build the knowledge graph on top of SogouQdb, a distributed search engine developed by Sogou Web Search Department, which can be easily scaled to support petabytes of data. As a supplement to the search engine, we also introduce a series of models to support inference and graph based querying. Currently, the data of Sogou knowledge graph that are collected from 136 different websites and constantly updated consist of 54 million entities and over 600 million entity links. We also introduce three applications of knowledge graph in Sogou Inc.: entity detection and linking, knowledge based question answering and knowledge based dialog system. These applications have been used in Web search products to help user acquire information more efficiently.


Author(s):  
Sabina Katalnikova ◽  
Leonids Novickis

In connection with the transition to a knowledge-based economy, at a time when a key factor in the development of society is the accumulated human knowledge and skills, as well as the availability of a wide range of users, intelligent systems are becoming very popular. Accordingly, the demand of the ergonomic and effective means of designing this class system is growing as well. The most time-consuming and most important stage of intelligent system development is the formation of the system knowledge base which ultimately determines the efficiency and quality of the entire intelligent system. Knowledge representation and processing models and methods as well as the intelligent system development techniques operating on the basis of these methods and models have a crucial role in relation to this. The article explores the different aspects of intelligent collaborative educational systems, describes the overall structure of an intelligent collaborative educational system and reflects the different steps of development the system.


Author(s):  
Pat Langley

Modern introductory courses on AI do not train students to create intelligent systems or provide broad coverage of this complex field. In this paper, we identify problems with common approaches to teaching artificial intelligence and suggest alternative principles that courses should adopt instead. We illustrate these principles in a proposed course that teaches students not only about component methods, such as pattern matching and decision making, but also about their combination into higher-level abilities for reasoning, sequential control, plan generation, and integrated intelligent agents. We also present a curriculum that instantiates this organization, including sample programming exercises and a project that requires system integration. Participants also gain experience building knowledge-based agents that use their software to produce intelligent behavior.


2010 ◽  
Vol 21 (1, 2) ◽  
pp. 1-3 ◽  
Author(s):  
I. Lovrek ◽  
R.J. Howlett ◽  
C.-P. Lim ◽  
L.C. Jain ◽  
G. Phillips-Wren

1988 ◽  
Vol 21 (10) ◽  
pp. 307-311 ◽  
Author(s):  
Clive Smallman

The intelligent condition monitoring of industrial plant is a rapidly expanding area of research. It combines two radically different disciplines: classical condition monitoring and intelligent knowledge-based systems. The paper presents an overview of the areas of orthodox condition monitoring systems, intelligent knowledge-based systems and intelligent condition monitoring. The paper also includes two examples of the diverse work underway in this area. Finally, there is a discussion of a current British Gas intelligent condition monitoring project, which is investigating the application of intelligent systems techniques to condition monitoring of gas compressor engines. This features a detailed summary of a particular element of the problem area. In addition the nature of the future development of this system is also discussed.


Author(s):  
S Lu

This paper describes the application, through examples and comparisons, of artificial intelligence including neural networks, fuzzy logic, genetic algorithms in three levels of computer aided boiler design: design by mathematical modelling, design by optimization and design by knowledge-based systems. It reviews the state-of-the-art situation and trends for future development in boiler design practice.


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