"This book provides readers with an in-depth compendium of current issues, trends, and technologies in association rule mining"--Provided by publisher.

This book provides a comprehensive introduction and practical look at the concepts and techniques readers need to get the most out of their data in real-world, large-scale data mining projects. It also guides readers through the data-analytic thinking necessary for extracting useful knowledge and business value from the data. The book is based on the Soft Computing and Data Mining (SCDM-16) conference, which was held in Bandung, Indonesia on August 18th–20th 2016 to discuss the state of the art in soft computing techniques, and offer participants sufficient knowledge to tackle a wide range of complex systems. The scope of the conference is reflected in the book, which presents a balance of soft computing techniques and data mining approaches. The two constituents are introduced to the reader systematically and brought together using different combinations of applications and practices. It offers engineers, data analysts, practitioners, scientists and managers the insights into the concepts, tools and techniques employed, and as such enables them to better understand the design choice and options of soft computing techniques and data mining approaches that are necessary to thrive in this data-driven ecosystem.

The two-volume set LNAI 7301 and 7302 constitutes the refereed proceedings of the 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2012, held in Kuala Lumpur, Malaysia, in May 2012. The total of 20 revised full papers and 66 revised short papers were carefully reviewed and selected from 241 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD-related areas. The papers are organized in topical sections on supervised learning: active, ensemble, rare-class and online; unsupervised learning: clustering, probabilistic modeling in the first volume and on pattern mining: networks, graphs, time-series and outlier detection, and data manipulation: pre-processing and dimension reduction in the second volume.

There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

This book constitutes the refereed proceedings of the 6th International Conference on Data Science, ICDS 2019, held in Ningbo, China, during May 2019. The 64 revised full papers presented were carefully reviewed and selected from 210 submissions. The research papers cover the areas of Advancement of Data Science and Smart City Applications, Theory of Data Science, Data Science of People and Health, Web of Data, Data Science of Trust and Internet of Things.

This two volume set LNCS 8055 and LNCS 8056 constitutes the refereed proceedings of the 24th International Conference on Database and Expert Systems Applications, DEXA 2013, held in Prague, Czech Republic, August 23-29, 2013. The 43 revised full papers presented together with 33 short papers, and 3 keynote talks, were carefully reviewed and selected from 174 submissions. These papers discuss a range of topics including: search queries; indexing; discovery of semantics; parallel processing; XML and RDF; enterprise models; query evaluation and optimization; semantic Web; sampling; industrial applications; communities; AI and databases; matching and searching; information extraction; queries, streams, and uncertainty, storage and compression; query processing; security; distributed data processing; metadata modeling and maintenance; pricing and recommending; and security and semantics.

The two-volume set LNCS 7289 and 7290 constitutes the refereed proceedings of the 11th International IFIP TC 6 Networking Conference held in Prague, Czech Republic, in May 2012. The 64 revised full papers presented were carefully reviewed and selected from a total of 225 submissions. The papers feature innovative research in the areas of network architecture, applications and services, next generation Internet, wireless and sensor networks, and network science. The second volume includes 32 papers and is organized in topical sections on video streaming, peer to peer, interdomain, security, cooperation and collaboration, DTN and wireless sensor networks, and wireless networks.

This book constitutes the refereed proceedings of the IFIP TC 5 International Conference on Digital Product and Process Development Systems, NEW PROLAMAT 2013, held in Dresden, Germany, in October 2013. The conference succeeds the International Conference on Programming Languages for Machine Tools, PROLAMAT 2006, held in Shanghai, China in 2006. In order to demonstrate the new orientation toward IT innovations, the acronym PROLAMAT has been changed into NEW PROLAMAT and is now interpreted as Project Research on Leading-Edge Applications and Methods for Applied Technology. The 42 revised papers were carefully reviewed and selected for inclusion in the volume. They have been organized in the following topical sections: digital product and process development; additive manufacturing; quality management; standardization and knowledge management developments; and simulation of procedures and processes.

This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions. This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns. A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.

Provides comprehensive coverage on recidivism risk/needs assessment tools Correctional and healthcare professionals around the world utilize structured instruments referred to as risk/needs assessment tools to predict the likelihood that an offender will recidivate. Such tools have been found to provide accurate and reliable evaluations and are widely used to assess, manage, and monitor offenders both institutionally as well as in the community. By identifying offenders in need of different levels of intervention, examining causal risk factors, and individualizing case management plans, risk/needs assessment tools have proven invaluable in addressing the public health issue of recidivism. Recidivism Risk/Needs Assessment Tools brings together the developers of the most commonly-used risk/needs assessment tools to provide a comprehensive overview of their development, peer-reviewed research literature, and practical application. Written by the leading professionals in the field of risk/needs assessment, the book provides chapters on: Recidivism Risk Assessment in the 21st Century; Performance of Recidivism Risk Assessment Instruments in Correctional Settings; Correctional Offender Management Profiles for Alternative Sanctions (COMPAS); the Federal Post-Conviction Risk Assessment Instrument; the Inventory of Offender Risks, Needs, and Strengths (IORNS); the Level of Service (LS) Instruments; the Ohio Risk Assessment System (ORAS); the Self-Appraisal Questionnaire (SAQ); the Service Planning Instrument (SPIn); the Static Risk Offender Needs Guide-Revised (STRONG-R); the Offender Group Reconviction Scale (OGRS); the Forensic Operationalized Therapy/Risk Evaluation System (FOTRES); the RisCanvi; and more. Systematically identifies currently-validated recidivism risk/needs assessment tools Reviews research on recidivism risk/needs assessment tools used internationally Each chapter presents sufficient detail to decide whether a given recidivism risk/needs assessment tool is right for your practice Recidivism Risk/Needs Assessment Tools is ideal for correctional, probation and parole, and behavioral health professionals.