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 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 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."