Proceedings of the Second International Conference on Knowledge Discovery and Data Mining
One of the greatest challenges facing organizations and individuals is how to turn their rapidly expanding data stores into accessible, and actionable knowledge. While advances on data storage and retrieval continue at a breakneck pace, the same cannot be asserted about the advances in information and knowledge extraction from large data sets. Underlying the need to convert their data into actionable knowledge, organizations have started an aggressive effort to deploy KDD applications. Many such applications are now in production in industries such as finance, insurance, retail, telecommunications, health care, astronomy, planetary sciences, biology, and so forth, and some early adopters are reaping significant financial benefit. The papers in this proceedings represent research from fields such as pattern recognition, statistics, artificial intelligence, very large databases, and visualization. All the research shares a set of core issues: representation of discovered knowledge, search complexity, the use of prior knowledge, statistical inference, algorithms that scale to analysis of massive amounts of data both in size and dimensionality, managing uncertainty, and interactive (human-oriented) presentation. The research in this book aims to provide the reader with a clear understanding of what represents the state of the art, and the state of practice in each of the various disciplines comprising KDD.