Abstract
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.
Reference30 articles.
1. A Domain Ontology For Data Collections Of The Accounting System in : International Conference On Informatics In Economy;Avram;Romania,2013
2. Fast algorithms for mining association rules in large databases in : Proceedings of the th on Very Large Data Bases Chile;Agrawal;International Conference VLDB,1994
3. Using Linear Algebra for Intelligent Information Retrieval;Berry;SIAM Review,1995
4. Rough sets applied to the RoughCast system for steel castings Intelligent Information and Database Systems in : Springer Lecture Notes in;Kluska;Computer Science,2011
5. Recognition of thermal images of direct current motor with application of Area Perimeter Vector and Bayes Classifier;Glowacz;Measurement Science Review,2015
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献