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Knowledge existing in modern information systems usually comes from many sources and is mapped in many ways. There is a real need for representing “knowledge pieces” as rather universal objects that should fit to multi-purpose a- ing systems. According to great number of information system’s tasks, knowledge representation is more or less detailed (e.g. some level of its granularity is - sumed). The main goal of this paper is to present chosen aspects of expressing granularity of knowledge implemented in intelligent systems. One of the main r- sons of granularity phenomena is diversification of knowledge sources, therefore the next section is devoted to this issue. 2. Heterogeneous Knowledge as a Source for Intelligent Systems Knowledge, the main element of so-called intelligent applications and systems, is very often heterogeneous. This heterogeneity concerns the origin of knowledge, its sources as well as its final forms of presentation. In this section the selected c- teria of knowledge differentiation will be presented, in the context of potential sources of knowledge acquisition. In Fig. 1 an environment of intelligent systems is shown, divided into different knowledge sources for the system. Fig. 1. Potential knowledge sources for intelligent information/reasoning system. Source: own elaboration based on (Mach, 2007) p. 24.
This volume comprises the 6th IFIP International Conference on Intelligent Infor- tion Processing. As the world proceeds quickly into the Information Age, it encounters both successes and challenges, and it is well recognized nowadays that intelligent information processing provides the key to the Information Age and to mastering many of these challenges. Intelligent information processing supports the most - vanced productive tools that are said to be able to change human life and the world itself. However, the path is never a straight one and every new technology brings with it a spate of new research problems to be tackled by researchers; as a result we are not running out of topics; rather the demand is ever increasing. This conference provides a forum for engineers and scientists in academia and industry to present their latest research findings in all aspects of intelligent information processing. This is the 6th IFIP International Conference on Intelligent Information Processing. We received more than 50 papers, of which 35 papers are included in this program as regular papers and 4 as short papers. We are grateful for the dedicated work of both the authors and the referees, and we hope these proceedings will continue to bear fruit over the years to come. All papers submitted were reviewed by two referees. A conference such as this cannot succeed without help from many individuals who contributed their valuable time and expertise.
Humans employ mostly natural languages in describing and representing problems, c- puting and reasoning, arriving at ?nal conclusions described similarly as words in a natural language or as the form of mental perceptions. To make machines imitate humans’ mental activities, the key point in terms of machine intelligence is to process uncertain information by means of natural languages with vague and imprecise concepts. Zadeh (1996a) proposed a concept of Computing with Words (CWW) to model and c- pute with linguistic descriptions that are propositions drawn from a natural language. CWW, followed the concept of linguistic variables (Zadeh, 1975a,b) and fuzzy sets (Zadeh, 1965), has been developed intensively and opened several new vast research ?elds as well as applied in various areas, particularly in the area of arti?cial intelligence. Zadeh (1997, 2005) emphasized that the core conceptions in CWW are linguistic variables and fuzzy logic (or approximate reasoning). In a linguistic variable, each linguistic value is explained by a fuzzy set (also called semantics of the linguistic value), its membership function is de?ned on the universe of discourse of the linguistic variable. By fuzzy sets, linguistic information or statements are quanti?ed by membership functions, and infor- tion propagation is performed by approximate reasoning. The use of linguistic variables implies processes of CWW such as their fusion, aggregation, and comparison. Different computational approaches in the literature addressed those processes (Wang, 2001; Zadeh and Kacprzyk, 1999a, b). Membership functions are generally at the core of many fuzzy-set theories based CWW.
Intelligent Information Processing presents new research with special emphasis on knowledge-based system architecture and intelligent information management. The following topics are addressed: -Agent-based Computing; -Semantic Web and Learning; -Ontology Management; -Semantic Web Architecture; -Knowledge-engineering Frameworks; -Knowledge-system Structure; -Data Mining; -Methods and Tools for Identifying Communities of Practice; and -Implementing Problem Solvers.
Intelligent Information Processing supports the most advanced productive tools that are said to be able to change human life and the world itself. This book presents the proceedings of the 4th IFIP International Conference on Intelligent Information Processing. This conference provides a forum for engineers and scientists in academia, university and industry to present their latest research findings in all aspects of Intelligent Information Processing.
This book constitutes the refereed proceedings of the 10th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2018, held in Nanning, China, in October 2018. The 37 full papers and 8 short papers presented were carefully reviewed and selected from 80 submissions. They are organized in topical sections on machine learning, deep learning, multi-agent systems, neural computing and swarm intelligence, natural language processing, recommendation systems, social computing, business intelligence and security, pattern recognition, and image understanding.
The international conference Intelligent Information Processing and Web Mining IIS:IIPWM’05, organized in Gda?sk-Sobieszewo on 13–16th June, 2005, was a continuation of a long tradition of conferences on applications of Arti?cial Intelligence (AI) in Information Systems (IS), organized by the Institute of Computer Science of Polish Academy of Sciences in cooperation with other scienti?c and business institutions. The Institute itself is deeply engaged in research both in AI and IS and many scientists view it as a leading institution both in fundamental and - plied research in these areas in Poland. The originators of this conference series, Prof. M. D?browski and Dr. M. Michalewicz had in 1992 a long-term goal of bringing together scientists and industry of di?erent braches from Poland and abroad to achieve a creative synthesis. One can say that their dream has come to reality. Scientists from ?ve continents made their subm- sions to this conference. A brief look at the a?liations makes international cooperation visible. The research papers have either a motivation in c- crete applications or are o?-springs of some practical requests. This volume presents the best papers carefully chosen from a large set of submissions (about 45%). At this point we would like to express our thanks to the m- bers of Programme Committee for their excellent job. Also we are thankful to the organizers of the special sessions accompanying this conference: Jan Komorowski, Adam Przepiórkowski, Zbigniew W.
This book reports on new theories and applications in the field of intelligent systems and computing. It covers computational and artificial intelligence methods, as well as advances in computer vision, current issues in big data and cloud computing, computation linguistics, and cyber-physical systems. It also reports on important topics in intelligent information management. Written by active researchers, the respective chapters are based on selected papers presented at the XIV International Scientific and Technical Conference on Computer Science and Information Technologies (CSIT 2019), held on September 17–20, 2019, in Lviv, Ukraine. The conference was jointly organized by the Lviv Polytechnic National University, Ukraine, the Kharkiv National University of Radio Electronics, Ukraine, and the Technical University of Lodz, Poland, under patronage of Ministry of Education and Science of Ukraine. Given its breadth of coverage, the book provides academics and professionals with extensive information and a timely snapshot of the field of intelligent systems, and is sure to foster new discussions and collaborations among different groups.
The book deals with several key aspects of developing technologies in information processing systems. It explains various problems related to advanced image processing systems and describes some of the latest state-of-the-art techniques in solving them. Particularly, the recent advances in image and video processing are covered thoroughly with real-life applications. Some of the latest topics like rough fuzzy hybridization and knowledge reuse in computational intelligence are included adequately.
This book features papers presented at IIH-MSP 2018, the 14th International Conference on Intelligent Information Hiding and Multimedia Signal Processing. The scope of IIH-MSP included information hiding and security, multimedia signal processing and networking, and bio-inspired multimedia technologies and systems. The book discusses subjects related to massive image/video compression and transmission for emerging networks, advances in speech and language processing, recent advances in information hiding and signal processing for audio and speech signals, intelligent distribution systems and applications, recent advances in security and privacy for multimodal network environments, multimedia signal processing, and machine learning. Presenting the latest research outcomes and findings, it is suitable for researchers and students who are interested in the corresponding fields. IIH-MSP 2018 was held in Sendai, Japan on 26–28 November 2018. It was hosted by Tohoku University and was co‐sponsored by the Fujian University of Technology in China, the Taiwan Association for Web Intelligence Consortium in Taiwan, and the Swinburne University of Technology in Australia, as well as the Fujian Provincial Key Laboratory of Big Data Mining and Applications (Fujian University of Technology) and the Harbin Institute of Technology Shenzhen Graduate School in China.