This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem. Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented. In addition, the book provides an overview of approaches to handling large collections of objects in a reasonable time. In particular, it addresses grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches, especially those used for community detection.
This edited book contains articles accepted for presentation during the conference "Intelligent Information Systems 2005 (IIS 2005) - New Trends in Intelligent Information Processing and Web Mining" held in Gdansk, Poland, on June 13-16, 2005. Special attention is devoted to the newest developments in the areas of Artificial Immune Systems, Search engines, Computational Linguistics and Knowledge Discovery. The focus of this book is also on new computing paradigms including biologically motivated methods, quantum computing, DNA computing, advanced data analysis, new machine learning paradigms, reasoning technologies, natural language processing and new optimization techniques.
This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem. Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented. In addition, the book provides an overview of approaches to handling large collections of objects in a reasonable time. In particular, it addresses grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches, especially those used for community detection.
This volume contains articles accepted for presentation during The Intelligent Information Systems Symposium IIS'2002 which was held in Sopot, Poland, on June 3-6, 2002. This is eleventh, in the order, symposium organized by the Institute of Computer Science of Polish Academy of Sciences and devoted to new trends in (broadly understood) ArtificialIntelligence. The meetings started back to 1992. With small initial audience, workshops in the series grew to an important meeting of Polish and foreign scientists working at the universities in Europe, Asia and the Northern America. Over years, the workshops transformed into regular symposia devoted to latest trends in 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 Evolutionary Algorithms). At present, about 50-60 papers are accepted each year. Besides, for several years now, the symposia are accompanied by a number of tutorials, given by the outstanding scientists in their domain. The main topics of this year symposium included: • decision trees and other classifier systems • neural network and biologiccally motivated systems • clustering methods • handling imprecision and uncertainty • deductive, distributed and agent-based systems We were pleased to see the continuation of the last year trend towards an increase in the number of co-operative contributions and in the number and diversity of practical applications of theoretical research.
This edited book contains articles accepted for presentation during the conference "Intelligent Information Systems 2005 (IIS 2005) - New Trends in Intelligent Information Processing and Web Mining" held in Gdansk, Poland, on June 13-16, 2005. Special attention is devoted to the newest developments in the areas of Artificial Immune Systems, Search engines, Computational Linguistics and Knowledge Discovery. The focus of this book is also on new computing paradigms including biologically motivated methods, quantum computing, DNA computing, advanced data analysis, new machine learning paradigms, reasoning technologies, natural language processing and new optimization techniques.
This volume contains articles accepted for presentation during The Intelligent Information Systems Symposium I1S'2000 which was held in Bystra, Poland, on June 12-16, 2000. This is ninth, in the order, symposium organized by the Institute of Computer Science of Polish Academy of Sciences and 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 uni versities in Europe and USA. 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 (Le. Fuzzy and Rough Sets, Bayesian Networks, Neural Networks and Evolutionary Algorithms). At present, about 50 papers prepared by researches from Poland and other countries are usually presented. Besides, for several years now, the symposia are accompanied by a number of tutorials, given by the outstanding scientists in their domain. Up to this year the proceedings were published as our local publication and they were distributed among the scientific libraries. We feel however, that the subject matter as well as the quality of papers is sufficient to present the proceedings to a broader scientific audience.
This edited book contains articles accepted for presentation during The Intelligent Information Processing and Web Mining Conference IIS:IIPWM ́03 held in Zakopane, Poland, on June 2-5, 2003. A lot of attention is devoted to the newest developments in the area of Artificial Intelligence with special calls for contributions on artificial immune systems and search engines. This book will be a valuable source for further research in the fields of data mining, intelligent information processing, immunogenetics, machine learning, or language processing for search engines.
The book offers a selection of papers presented at the international symposium Intelligent Information Systems X held in Zakopane, Poland. The papers report on progress in theory and applications of broadly understood artificial intelligence, including machine learning, knowledge discovery, knowledge based systems and reasoning, intelligent statistical analysis and soft computing (i.e. fuzzy and rough sets, neural networks, evolutionary algorithms and artificial immune systems). Interesting new theoretical results are presented and their practical applicability demonstrated. The volume also suggests challenging new research issues.
This edited book contains articles accepted for presentation during The Intelligent Information Processing and Web Mining Conference IIS:IIP WM¿04 held in Zakopane, Poland, on May 17-20, 2004. Considerable attention is devoted to the newest developments in the area of Artificial Intelligence with special calls for contributions on Web mining. This book will be a valuable source for further research in the fields of data mining, intelligent information processing, machine learning, computational linguistics, or natural language processing for search engines.
This volume contains selected papers, presented at the international conference on Intelligent Information Processing and Web Mining Conference IIS:IIPWM'06, organized in Ustro (Poland), 2006. The submitted papers cover new computing paradigms, among others in biologically motivated methods, advanced data analysis, new machine learning paradigms, natural language processing, new optimization technologies, applied data mining using statistical and non-standard approaches.
This will help us customize your experience to showcase the most relevant content to your age group
Please select from below
Login
Not registered?
Sign up
Already registered?
Success – Your message will goes here
We'd love to hear from you!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.