الصفحة 1
الصفحة 1
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Multiple-Aspect Analysis of Semantic Trajectories ; First International Workshop, MASTER 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Proceedings

This book constitutes the refereed post-conference proceedings of the First International Workshop on Multiple-Aspect Analysis of Semantic Trajectories, MASTER 2019, held in conjunction with the 19th European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, in Würzburg, Germany, in September 2019.

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Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases

The present volume provides a collection of seven articles containing new and high quality research results demonstrating the significance of Multi-objective Evolutionary Algorithms (MOEA) for data mining tasks in Knowledge Discovery from Databases (KDD). These articles are written by leading experts around the world. It is shown how the different MOEAs can be utilized, both in individual and integrated manner, in various ways to efficiently mine data from large databases.

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Mobility, data mining and privacy : Geographic knowledge discovery

This book assesses this research frontier from a computer science perspective, investigating the various scientific and technological issues, open problems, and roadmap. The editors manage a research project called GeoPKDD, Geographic Privacy-Aware Knowledge Discovery and Delivery, funded by the EU Commission and involving 40 researchers from 7 countries, and this book tightly integrates and relates their findings in 13 chapters covering all related subjects, including the concepts of movement data and knowledge discovery from movement data; privacy-aware geographic knowledge discovery; wireless network and next-generation mobile technologies; trajectory data models, systems and warehouses; privacy and security aspects of technologies and related regulations; querying, mining and reasoning on spatiotemporal data; and visual analytics methods for movement data.

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Mining Complex Data ; ECML/PKDD 2007 Third International Workshop, MCD 2007, Warsaw, Poland, September 17-21, 2007, Revised Selected Papers

This book constitutes the refereed proceedings of the Third International Workshop on Mining Complex Data, MCD 2007, held in Warsaw, Poland, in September 2007, co-located with ECML and PKDD 2007.The 20 revised full papers presented were carefully reviewed and selected; they present original results on knowledge discovery from complex data. In contrast to the typical tabular data, complex data can consist of heterogenous data types, can come from different sources, or live in high dimensional spaces. All these specificities call for new data mining strategies.

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Intelligence and Security Informatics ; Vol. 3917 ; International Workshop, WISI 2006, Singapore, April 9, 2006, Proceedings

Intelligence and security informatics (ISI) can be broadly defined as the study of the development and use of advanced information technologies and systems for national and international security-related applications. The First and Second Symposiums on ISI were held in Tucson, Arizona, in 2003 and 2004, respectively. In 2005, the IEEE International Conference on ISI was held in Atlanta, Georgia. These ISI conferences brought together academic researchers, law enforcement and intelligence experts, information technology consultants and practitioners to discuss their research and practice related to various ISI topics including ISI data management, data and text mining for ISI applications, terrorism informatics, deception detection, terrorist and criminal social network analysis, crime analysis, monitoring and surveillance, policy studies and evaluation, and information assurance, among others. We continued these stream of ISI conferences by organizing the Workshop on Intelligence and Security Informatics (WISI 2006) in conjunction with the Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006).

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Emerging Technologies in Knowledge Discovery and Data Mining ; PAKDD 2007 International Workshops, Nanjing, China, May 22-25, 2007, Revised Selected Papers

The objective of this volume is to offer the excellent presentations to the public, and to promote the study exchange among researchers worldwide.The first part of this volume contains industrial track. This track was organized to attract papers on new technology trends and real-world solutions in different industry sectors. The succeeding chapters include Data Mining for Biomedical Applications aimed at attracting top researchers, practitioners and students from around the world to discuss data mining applications in the field of bioinformatics

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Database and expert systems applications ; DEXA 2020 International workshops BIOKDD, IWCFS and MLKgraphs, Bratislava, Slovakia, September 14–17, 2020, Proceedings

This volume constitutes the refereed proceedings of the three workshops held at the 31st International Conference on Database and Expert Systems Applications, DEXA 2020, held in September 2020: The 11th International Workshop on Biological Knowledge Discovery from Data, BIOKDD 2020, the 4th International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems, IWCFS 2020, the 2nd International Workshop on Machine Learning and Knowledge Graphs, MLKgraphs2019. Due to the COVID-19 pandemic the conference and workshop were held virtually. The 10 papers were thoroughly reviewed and selected from 15 submissions, and discuss a range of topics including: knowledge discovery, biological data, cyber security, cyber-physical system, machine learning, knowledge graphs, information retriever, data base, and artificial intelligent.

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Data Mining for Biomedical Applications ; PAKDD 2006 Workshop, BioDM 2006, Singapore, April 9, 2006, Proceedings

This book constitutes the refereed proceedings of the International Workshop on Data Mining for Biomedical Applications, BioDM 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 14 revised full papers presented together with 1 keynote talks were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections on protein-protein interactions, database and search, bio data clustering, and in-silico diagnosis.

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Data mining and Knowledge discovery handbook

Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security.

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Machine Learning: ECML 2007 ; 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings

The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the ?rst joint conference in Freiburg, 2001. The European Conference on Machine Learning (ECML) traces its origins to 1986, when the ?rst European Working Session on Learning was held in Orsay, France. The European Conference on Principles and Practice of KnowledgeDiscoveryinDatabases(PKDD) was?rstheldin1997inTrondheim, Norway.

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Machine Learning: ECML 2006 ; 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings

This book constitutes the refereed proceedings of the 17th European Conference on Machine Learning, ECML 2006, held in Berlin, Germany in September 2006, jointly with PKDD 2006. The 46 revised full papers and 36 revised short papers presented together with abstracts of 5 invited talks were carefully reviewed and selected from 564 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.

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Machine Learning and Knowledge Discovery in Databases ; European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part II

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.

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Machine Learning and Knowledge Discovery in Databases ; European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I

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.

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Machine learning and data mining for sports analytics ; 7th international workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings

Constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.

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Machine Learning : ECML 2005 ; 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings

The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3–7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work required a tremendous e?ort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qualified independent reviews per paper (with very few exceptions) and one additional overall input from one of the Area Chairs. After the authors’ responses and the online discussions for many of the papers, we arrived at the ?nal selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall.

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Local Pattern Detection ; International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers

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 field knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the field offers the opportunity to combine the expertise of different fields into a common objective. Moreover, within each field diverse methods have been developed and justified with respect to different quality criteria. We have to investigate how these methods can contributet o solving the problem of KDD. Traditionally, KDD was seeking to end global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to end only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new field of local patterns.

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Knowledge Discovery in Life Science Literature ; International Workshop, KDLL 2006, Singapore, April 9, 2006, Proceedings

Constitutes the refereed proceedings of the International Workshop on Knowledge Discovery in Life Science Literature, KDLL 2006, held in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 12 revised full papers presented together with two invited talks were carefully reviewed and selected for inclusion in the book. The papers cover all topics of knowledge discovery in life science data.

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Knowledge Discovery in Inductive Databases ; Vol.3377 : 3rd International Workshop, KDID 2004, Pisa, Italy, September 20, 2004, Revised Selected and Invited Papers

Cnstitutes the thoroughly refereed joint postproceedings of the Third International Workshop on Knowledge Discovery in Inductive Databases, KDID 2004, held in Pisa, Italy in September 2004 in association with ECML/PKDD. Inductive Databases support data mining and the knowledge discovery process in a natural way. In addition to usual data, an inductive database also contains inductive generalizations, like patterns and models extracted from the data. This book presents nine revised full papers selected from 23 submissions during two rounds of reviewing and improvement together with one invited paper. Various current topics in knowledge discovery and data mining in the framework of inductive databases are addressed.

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Knowledge Discovery in Databases : PKDD 2007 ; 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings

The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the ?rst joint conference in Freiburg, 2001. The European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) was?rstheldin1997inTrondheim, Norway.

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Knowledge discovery in databases : PKDD 2006 ; 10th European Conference on Principles and practice of knowledge discovery in databases, Berlin, Germany, September 18-22, 2006, Proceedings

The European Conference on Principles and Practice of Knowledge Discovery in Databases celebrates its tenth anniversary ; the first PKDD took place in 1997 in Trondheim, Norway. Over the years, the ECML/PKDD series has evolved into one of the largest and most selective international conferences in these areas, the only one that provides a common forum for the two closely related ?elds. In 2006, the 6th collocated ECML/PKDD took place during September 18-22, when the Humboldt-Universität zu Berlin hosted the 17th European Conference on Machine Learning (ECML) and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD). The successful model of a hierarchical reviewing process that was introduced last year for the ECML/PKDD 2005 in Porto has been taken over in 2006.

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