Conceptual basis for developing of trainig models in complex system software assembling generator

This paper presents conceptual basis for developing of training models of interactive assembling system for automatic building of application software systems, obtained during practical works over "Design and architecture of software systems" and "Object-oriented analysis and design" courses. The system is intended for practical demonstration of basic stages and operations in development of complex and critical software. This also includes a consideration of solutions for some substantial problems of complex systems software generation, such as: program module compatibility, formalization of computer interaction and choosing of formal model for human machine interface. In addition, several training model implementations are provided.Keywords: software generator, training models, interactive system

An overview of computer-based natural language processing

Computer based Natural Language Processing (NLP) is the key to enabling humans and their computer based creations to interact with machines in natural language (like English, Japanese, German, etc., in contrast to formal computer languages). The doors that such an achievement can open have made this a major research area in Artificial Intelligence and Computational Linguistics. Commercial natural language interfaces to computers have recently entered the market and future looks bright for other applications as well. This report reviews the basic approaches to such systems, the techniques utilized, applications, the state of the art of the technology, issues and research requirements, the major participants and finally, future trends and expectations. It is anticipated that this report will prove useful to engineering and research managers, potential users, and others who will be affected by this field as it unfolds

Machine learning : techniques and foundations

The field of machine learning studies computational methods for acquiring new knowledge, new skills, and new ways to organize existing knowledge. In this paper we present some of the basic techniques and principles that underlie AI research on learning, including methods for learning from examples, learning in problem solving, learning by analogy, grammar acquisition, and machine discovery. In each case, we illustrate the techniques with paradigmatic examples

Physical Object Representation and Generation: A Survey of Programs For Semantic-Based Natural Language Processing

This article surveys a portion of the field of natural language processing. The main areas considered are those dealing with representation schemes, particularly work on physical object representation, and generalization processes driven by natural language understanding. The emphasis of this article is on conceptual representation of objects based on the semantic interpretation of natural language input. Six programs serve as case studies for guiding the course of the article. Within the framework of describing each of these programs, several other programs, ideas, and theories that are relevant to the program in focus are presented