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Intelligent Information Processing XI by Zhongzhi Shi,Jean-Daniel Zucker,Bo An Pdf
This book constitutes the refereed proceedings of the 12th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2022, held in Qingdao, China, in July 2022. The 37 full papers and 6 short papers presented were carefully reviewed and selected from 57 submissions. They are organized in topical sections on Machine Learning, Data Mining, Multiagent Systems, Social Computing, Blockchain Technology, Game Theory and Emotion, Pattern Recognition, Image Processing and Applications.
Intelligent Information Processing X by Zhongzhi Shi,Sunil Vadera,Elizabeth Chang Pdf
This book constitutes the refereed proceedings of the 11th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2020, held in Hangzhou, China, in July 2020. The 24 full papers and 5 short papers presented were carefully reviewed and selected from 36 submissions. They are organized in topical sections on machine learning; multi-agent system; recommendation system; social computing; brain computer integration; pattern recognition; and computer vision and image understanding.
Intelligent Information Processing by Mark Musen,Bernd Neumann,Rudi Studer Pdf
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 II by Qing He Pdf
Data Mining is the process of posing queries and extracting useful information, patterns and trends previously unknown from large quantities of data [Thu, 00]. It is the process where intelligent tools are applied in order to extract data patterns [JM, 01]. This encompasses a number of different technical approaches, such as cluster analysis, learning classification and association rules, and finding dependencies. Agents are defined as software entities that perform some set of tasks on behalf of users with some degree of autonomy. This research work deals about developing a automated data mining system which encompasses the familiar data mining algorithms using intelligent agents in object oriented databases and proposing a framework. Because the data mining system uses the intelligent agents, a new user will be able to interact with the data mining system without much data mining technical knowledge. This system will automatically select the appropriate data mining technique and select the necessary field needed from the database at the appropriate time without expecting the users to specify the specific technique and the parameters. Also a new framework is proposed for incorporating intelligent agents with automated data mining. One of the major goals in developing this system is to give the control to the computer for learning automatically by using intelligent agents.
Advances in Intelligent Information Processing by Bhabatosh Chanda,C. A. Murthy Pdf
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.
Intelligent Information Processing XI by Zhongzhi Shi,Jean-Daniel Zucker,Bo An Pdf
This book constitutes the refereed proceedings of the 12th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2022, held in Qingdao, China, in July 2022. The 37 full papers and 6 short papers presented were carefully reviewed and selected from 57 submissions. They are organized in topical sections on Machine Learning, Data Mining, Multiagent Systems, Social Computing, Blockchain Technology, Game Theory and Emotion, Pattern Recognition, Image Processing and Applications.
Intelligent Information Processing and Web Mining by Mieczyslaw A. Klopotek,Slawomir T. Wierzchon,Krzysztof Trojanowski Pdf
This volume contains articles accepted for presentation during The Intel ligent Information Processing and Web Mining Conference IIS:IIPWM'04 which was held in Zakopane, Poland, on May 17-20, 2004. This conference is a continuation of a series of 13 successful symposia and conferrences on Intel ligent Information Systems, organized by the Institute of Computer Science of Polish Academy of Sciences, devoted to new trends in (broadly understood) Artificial Intelligence. The idea of organizing such meetings dates back to 1992. Our main in tention guided the first, rather small-audience, workshop in the series was to resume the results gained in Polish scientific centers as well as contrast them with the research performed by Polish scientists working at the universities in Europe and USA and their foreign collaborators. This idea proved to be attractive enough that we decided to continue such meetings. As the years went by, the workshops has transformed into regular symposia devoted to such fields like Machine Learning, Knowledge Discovery, Natural Language Processing, Knowledge Based Systems and Reasoning, and Soft Computing (i. e. Fuzzy and Rough Sets, Bayesian Networks, Neural Networks and Evo lutionary Algorithms). At present, about 50 papers prepared by researches from Poland and other countries are usually presented. This year conference devotes much more attention to the newest devel opments in the area of Artificial Intelligence, related to broadly understood Web mining.
LINGUISTIC VALUES BASED INTELLIGENT INFORMATION PROCESSING by Pei Zheng,Ruan Da Pdf
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 IV by Eunikka Mercier-Laurent,David Leake Pdf
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.
Intelligent Information Processing III by K. Shimohara,D. Feng Pdf
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.
Recent Advances in Intelligent Information Hiding and Multimedia Signal Processing by Jeng-Shyang Pan,Akinori Ito,Pei-Wei Tsai,Lakhmi C. Jain Pdf
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.
Brain Storm Optimization Algorithms by Shi Cheng,Yuhui Shi Pdf
Brain Storm Optimization (BSO) algorithms are a new kind of swarm intelligence method, which is based on the collective behavior of human beings, i.e., on the brainstorming process. Since the introduction of BSO algorithms in 2011, many studies on them have been conducted. They not only offer an optimization method, but could also be viewed as a framework of optimization techniques. The process employed in the algorithms could be simplified as a framework with two basic operations: the converging operation and the diverging operation. A “good enough” optimum could be obtained through recursive solution divergence and convergence. The resulting optimization algorithm would naturally have the capability of both convergence and divergence. This book is primarily intended for researchers, engineers, and graduate students with an interest in BSO algorithms and their applications. The chapters cover various aspects of BSO algorithms, and collectively provide broad insights into what these algorithms have to offer. The book is ideally suited as a graduate-level textbook, whereby students may be tasked with the study of the rich variants of BSO algorithms that involves a hands-on implementation to demonstrate the utility and applicability of BSO algorithms in solving optimization problems.
Computer and Computing Technologies in Agriculture XI by Daoliang Li,Chunjiang Zhao Pdf
The two volumes IFIP AICT 545 and 546 constitute the refereed post-conference proceedings of the 11th IFIP WG 5.14 International Conference on Computer and Computing Technologies in Agriculture, CCTA 2017, held in Jilin, China, in August 2017. The 100 revised papers included in the two volumes were carefully reviewed and selected from 282 submissions. They cover a wide range of interesting theories and applications of information technology in agriculture. The papers focus on four topics: Internet of Things and big data in agriculture, precision agriculture and agricultural robots, agricultural information services, and animal and plant phenotyping for agriculture.
11th World Conference “Intelligent System for Industrial Automation” (WCIS-2020) by Rafik Aziz Aliev,Nodirbek Rustambekovich Yusupbekov,Janusz Kacprzyk,Witold Pedrycz,Fahreddin M. Sadikoglu Pdf
This book presents the proceedings of the 11th Scientific Conference “Intelligent systems for industrial automation,” WCIS-2020, held in Tashkent, Uzbekistan, on November 26–28, 2020. It includes contributions from diverse areas of intelligent industrial systems design as hybrid control systems, intelligent information systems, decision making under imperfect information and others. The topics of the papers include intelligent control systems, pattern recognition, Industry 4.0, information security, neural computing, fuzzy and evolutionary computation, decision making and support systems, modeling of chemical technological processes and others.
