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The rapid development and the growing penetration of information and communication technologies (ICT) provide tremendous opportunities for a wide and cost effective application of the ideas of participative democracy and public participation in government decision and policy making. ICT can drive dramatic transformations in the quantity and quality of communication and interaction of government organizations with citizens, revitalizing and strengthening the modern representative democracy which currently faces big problems of reduced citizens’ trust and involvement. This book deals with the application of these e-participation ideas in the special and ‘difficult’, and at the same time ...
The multi-volume set LNAI 13713 until 13718 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2022, which took place in Grenoble, France, in September 2022. The 236 full papers presented in these proceedings were carefully reviewed and selected from a total of 1060 submissions. In addition, the proceedings include 17 Demo Track contributions. The volumes are organized in topical sections as follows: Part I: Clustering and dimensionality reduction; anomaly detection; interpretability and explainability; ranking and recommender systems; transfer and multitask learning; Part II: Networks and graphs; knowledge grap...
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new ?eld knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the ?eld o?ers the opportunity to combine the expertise of di?erent ?elds intoacommonobjective.Moreover,withineach?elddiversemethodshave been developed and justi?ed with respect to di?erent quality criteria. We have toinvestigatehowthesemethods cancontributeto solvingthe problemof...
We are glad to present the proceedings of the 5th biennial conference in the Intelligent Data Analysis series. The conference took place in Berlin, Germany, August 28–30, 2003. IDA has by now clearly grown up. Started as a small si- symposium of a larger conference in 1995 in Baden-Baden (Germany) it quickly attractedmoreinterest(bothsubmission-andattendance-wise),andmovedfrom London (1997) to Amsterdam (1999), and two years ago to Lisbon. Submission ratesalongwiththeeverimprovingqualityofpapershaveenabledtheor- nizers to assemble increasingly consistent and high-quality programs. This year we were again overwhelmed by yet another record-breaking submission rate of 180 papers. At the Progr...
This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held, jointly with PKDD 2006. The book presents 46 revised full papers and 36 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers present a wealth of new results in the area and address all current issues in machine learning.
This book constitutes the refereed proceedings of the 8th International Conference on Electronic Government, EGOV 2009, held in Linz, Austria, in August/September 2008 within the DEXA 2009 conference cluster. The 34 revised full papers presented were carefully reviewed and selected from 119 submissions. The papers are organized in topical sections on reflecting e-government research, administrative reform and public sector modernization, performance management and evaluation, aspects in government-to-citizen interactions, and building blocks in e-government advancements.
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.
Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.
This book constitutes the refereed proceedings of the 6th International Conference on Discovery Science, DS 2003, held in Sapporo, Japan in October 2003. The 18 revised full papers and 29 revised short papers presented together with 3 invited papers and abstracts of 2 invited talks were carefully reviewed and selected from 80 submissions. The papers address all current issues in discovery science including substructure discovery, Web navigation patterns discovery, graph-based induction, time series data analysis, rough sets, genetic algorithms, clustering, genome analysis, chaining patterns, association rule mining, classification, content based filtering, bioinformatics, case-based reasoning, text mining, Web data analysis, and more.