Geographic Data Mining and Knowledge Discovery


Book Description

Advances in automated data collection are creating massive databases and a whole new field, Knowledge Discovery Databases (KDD), has emerged to develop new methods of managing and exploiting them. Geographic Data Mining and Knowledge Discovery is the interrogation of large databases using efficient computational methods. The unique challenges brought about by the storing of massive geographical databases - from high resolution satellite-based systems to data from intelligent transportation systems, for example - has led to the field of Geographical Knowledge Discovery (GKD). Geographic or spatial data mining is the exploration of these geographical information databases. Developed out of contributions to the highly-respected Varenius Project in 1999, this collection will be the definitive volume focusing on GKD and addresses the special challenges to be found in knowledge discovery and data mining from geographic databases.




Data Mining


Book Description

This comprehensive textbook on data mining details the unique steps of the knowledge discovery process that prescribes the sequence in which data mining projects should be performed, from problem and data understanding through data preprocessing to deployment of the results. This knowledge discovery approach is what distinguishes Data Mining from other texts in this area. The book provides a suite of exercises and includes links to instructional presentations. Furthermore, it contains appendices of relevant mathematical material.




Big Data Analytics and Knowledge Discovery


Book Description

This book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections similarity measure and clustering; data mining; social computing; heterogeneos networks and data; data warehouses; stream processing; applications of big data analysis; and big data.




Data Warehousing and Knowledge Discovery


Book Description

This book constitutes the refereed proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery, DaWak 2009 held in Linz, Austria in August/September 2009. The 36 revised full papers presented were carefully reviewed and selected from 124 submissions. The papers are organized in topical sections on data warehouse modeling, data streams, physical design, pattern mining, data cubes, data mining applications, analytics, data mining, clustering, spatio-temporal mining, rule mining, and OLAP recommendation.




Data Warehousing and Knowledge Discovery


Book Description

This book constitutes the refereed proceedings of the 10th International Conference on Data Warehousing and Knowledge Discovery, DaWak 2008, held in Turin, Italy, in September 2008. The 40 revised full papers presented were carefully reviewed and selected from 143 submissions. The papers are organized in topical sections on conceptual design and modeling, olap and cube processing, distributed data warehouse, data privacy in data warehouse, data warehouse and data mining, clustering, mining data streams, classification, text mining and taxonomy, machine learning techniques, and data mining applications.




Information Visualization in Data Mining and Knowledge Discovery


Book Description

This text surveys research from the fields of data mining and information visualisation and presents a case for techniques by which information visualisation can be used to uncover real knowledge hidden away in large databases.




Data Warehousing and Knowledge Discovery


Book Description

This book constitutes the refereed proceedings of the 5th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2003, held in Prague, Czech Republic in September 2003. The 41 revised full papers presented were carefully reviewed and selected from more than 130 submissions. The papers are organized in topical sections on data cubes and queries, multidimensional data models, Web warehousing, change detection, Web mining and association rules, association rules and decision trees, clustering, association rule mining, data analysis and discovery, ontologies and improving data quality, queries and data patterns, improving database query engines, and sampling and vector classification.




Big Data Analytics and Knowledge Discovery


Book Description

This volume LNCS 12925 constitutes the papers of the 23rd International Conference on Big Data Analytics and Knowledge Discovery, held in September 2021. Due to COVID-19 pandemic it was held virtually. The 12 full papers presented together with 15 short papers in this volume were carefully reviewed and selected from a total of 71 submissions. The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.




Data Warehousing and Knowledge Discovery


Book Description

For more than a decade, data warehousing and knowledge discovery technologies have been developing into key technologies for decision-making processes in com- nies. Since 1999, due to the relevant role of these technologies in academia and ind- try, the Data Warehousing and Knowledge Discovery (DaWaK) conference series have become an international forum where both practitioners and researchers share their findings, publish their relevant results and dispute in depth research issues and experiences on data warehousing and knowledge discovery systems and applications. The 7th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2005) continued series of successful conferences dedicated to these topics. In this edition, the conference tried to provide the right, logical balance between data warehousing and knowledge discovery. Regarding data warehousing, papers cover different relevant and still unsolved research problems, such as the modelling of ETL processes and integration problems, designing OLAP technologies from XML do- ments, modelling data warehouses and data mining applications together, impro- ments in query processing, partitioning and implementations. With regard to data mining, a variety of papers were presented on subjects including data mining te- niques, clustering, classification, text documents and classification, and patterns. These proceedings contain the technical papers that were selected for presentation at the conference. We received 196 abstracts, and finally received 162 papers from 38 countries, and the Program Committee eventually selected 51 papers, making an acceptance rate of 31.4 % of submitted papers.




Data Warehousing and Knowledge Discovery


Book Description

This book constitutes the refereed proceedings of the 8th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2006, held in conjunction with DEXA 2006. The book presents 53 revised full papers, organized in topical sections on ETL processing, materialized view, multidimensional design, OLAP and multidimensional model, cubes processing, data warehouse applications, mining techniques, frequent itemsets, mining data streams, ontology-based mining, clustering, advanced mining techniques, association rules, miscellaneous applications, and classification.