Measuring the Performance of a Model Semantic Knowledge-Base for Automation of Commonsense Reasoning

2021 ◽  
pp. 253-263
Author(s):  
Chandan Hegde ◽  
K. Ashwini
Keyword(s):  
Knowledge Base ◽  
Semantic Knowledge ◽  
Commonsense Reasoning ◽  
Semantic Knowledge Base

scholarly journals Formalization of Technological Knowledge in the Field of Metallurgy using Document Classification Tools Supported with Semantic Techniques

2017 ◽  
Vol 62 (2) ◽  
pp. 715-720 ◽  
Author(s):  
K. Regulski
Keyword(s):  
Knowledge Base ◽  
Latent Semantic Indexing ◽  
Semantic Knowledge ◽  
Technological Knowledge ◽  
Semantic Integration ◽  
Semantic Indexing ◽  
Text Documents ◽  
Semantic Techniques ◽  
Semantic Knowledge Base

AbstractThe process of knowledge formalization is an essential part of decision support systems development. Creating a technological knowledge base in the field of metallurgy encountered problems in acquisition and codifying reusable computer artifacts based on text documents. The aim of the work was to adapt the algorithms for classification of documents and to develop a method of semantic integration of a created repository. Author used artificial intelligence tools: latent semantic indexing, rough sets, association rules learning and ontologies as a tool for integration. The developed methodology allowed for the creation of semantic knowledge base on the basis of documents in natural language in the field of metallurgy.

scholarly journals Semantic Knowledge Base in Support of Activity Recognition in Smart Home Environments

2018 ◽  
Vol 7 (4.27) ◽  
pp. 67
Author(s):  
Abdul Syafiq Abdull Sukor ◽  
Ammar Zakaria ◽  
Norasmadi Abdul Rahim ◽  
Rossi Setchi
Keyword(s):  
Knowledge Base ◽  
Activity Recognition ◽  
Smart Home ◽  
Semantic Knowledge ◽  
Experimental Results ◽  
Semantic Knowledge Base ◽  
Main Components ◽  
Use Of Knowledge ◽  
Smart Home Environments ◽  
Home Systems

Activity recognition plays a major role in smart home technologies in providing services to users. One of the approaches to identify activity is through the use of knowledge-driven reasoning. This paper presents a framework of semantic activity recognition, which is used to support smart home systems to identify users’ activities based on the existing context. The framework consists of two main components: a semantic knowledge base and an activity recognition module. The knowledge base is represented using ontology and it is used to provide a semantic understanding of the environment in order to classify users’ patterns of activities. Experimental results show that the proposed approach can support the classification process and accurately infer users’ activities with the accuracy of 90.9%.  

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