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Author: Shichao Zhang Publisher: Springer Science & Business Media ISBN: 0857293885 Category : Computers Languages : en Pages : 237
Book Description
Many organizations have an urgent need of mining their multiple databases inherently distributed in branches (distributed data). In particular, as the Web is rapidly becoming an information flood, individuals and organizations can take into account low-cost information and knowledge on the Internet when making decisions. How to efficiently identify quality knowledge from different data sources has become a significant challenge. This challenge has attracted a great many researchers including the au thors who have developed a local pattern analysis, a new strategy for dis covering some kinds of potentially useful patterns that cannot be mined in traditional multi-database mining techniques. Local pattern analysis deliv ers high-performance pattern discovery from multiple databases. There has been considerable progress made on multi-database mining in such areas as hierarchical meta-learning, collective mining, database classification, and pe culiarity discovery. While these techniques continue to be future topics of interest concerning multi-database mining, this book focuses on these inter esting issues under the framework of local pattern analysis. The book is intended for researchers and students in data mining, dis tributed data analysis, machine learning, and anyone else who is interested in multi-database mining. It is also appropriate for use as a text supplement for broader courses that might also involve knowledge discovery in databases and data mining.
Author: Shichao Zhang Publisher: Springer Science & Business Media ISBN: 9781852337032 Category : Computers Languages : en Pages : 250
Book Description
The Web has emerged as a large, distributed data repository, and information on the Internet and in existing transaction databases can be analyzed for commercial gains in decision making. Therefore, how to efficiently identify quality knowledge from different data sources uncovers a significant challenge. This challenge has attracted wide interest from both academia and the industry. Knowledge Discovery in Multiple Databases provides a comprehensive introduction to the latest advancements in multi-database mining, and presents a local-pattern analysis framework for pattern discovery from multiple data sources. Based on this framework, data preparation techniques in multiple databases, an application-independent database classification for data reduction, and efficient algorithms for pattern discovery from multiple databases are described. Knowledge Discovery in Multiple Databases is suitable for researchers, professionals and students in data mining, distributed data analysis, and machine learning, who are interested in multi-database mining. It is also appropriate for use as a text supplement for broader courses that might involve knowledge discovery in databases and data mining.
Author: Joao Gama Publisher: CRC Press ISBN: 1439826129 Category : Business & Economics Languages : en Pages : 256
Book Description
Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents
Author: Khosrow-Pour, D.B.A., Mehdi Publisher: IGI Global ISBN: 1522575995 Category : Computers Languages : en Pages : 1946
Book Description
From cloud computing to data analytics, society stores vast supplies of information through wireless networks and mobile computing. As organizations are becoming increasingly more wireless, ensuring the security and seamless function of electronic gadgets while creating a strong network is imperative. Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics highlights the challenges associated with creating a strong network architecture in a perpetually online society. Readers will learn various methods in building a seamless mobile computing option and the most effective means of analyzing big data. This book is an important resource for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, and IT specialists seeking modern information on emerging methods in data mining, information technology, and wireless networks.
Author: Shichao Zhang Publisher: Springer Science & Business Media ISBN: 0857293885 Category : Computers Languages : en Pages : 237
Book Description
Many organizations have an urgent need of mining their multiple databases inherently distributed in branches (distributed data). In particular, as the Web is rapidly becoming an information flood, individuals and organizations can take into account low-cost information and knowledge on the Internet when making decisions. How to efficiently identify quality knowledge from different data sources has become a significant challenge. This challenge has attracted a great many researchers including the au thors who have developed a local pattern analysis, a new strategy for dis covering some kinds of potentially useful patterns that cannot be mined in traditional multi-database mining techniques. Local pattern analysis deliv ers high-performance pattern discovery from multiple databases. There has been considerable progress made on multi-database mining in such areas as hierarchical meta-learning, collective mining, database classification, and pe culiarity discovery. While these techniques continue to be future topics of interest concerning multi-database mining, this book focuses on these inter esting issues under the framework of local pattern analysis. The book is intended for researchers and students in data mining, dis tributed data analysis, machine learning, and anyone else who is interested in multi-database mining. It is also appropriate for use as a text supplement for broader courses that might also involve knowledge discovery in databases and data mining.
Author: Dimitrios Gunopulos Publisher: Springer ISBN: 3642237835 Category : Computers Languages : en Pages : 702
Book Description
This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.
Author: Joost N. Kok Publisher: Springer Science & Business Media ISBN: 3540749756 Category : Computers Languages : en Pages : 660
Book Description
This book constitutes the refereed proceedings of the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2007, held in Warsaw, Poland, co-located with ECML 2007, the 18th European Conference on Machine Learning. The 28 revised full papers and 35 revised short papers present original results on leading-edge subjects of knowledge discovery from conventional and complex data and address all current issues in the area.
Author: Jean-Francois Boulicaut Publisher: Springer ISBN: 354030116X Category : Computers Languages : en Pages : 578
Book Description
The proceedings of ECML/PKDD 2004 are published in two separate, albeit - tertwined, volumes:theProceedingsofthe 15thEuropeanConferenceonMac- ne Learning (LNAI 3201) and the Proceedings of the 8th European Conferences on Principles and Practice of Knowledge Discovery in Databases (LNAI 3202). The two conferences were co-located in Pisa, Tuscany, Italy during September 20-24, 2004. It was the fourth time in a row that ECML and PKDD were co-located. - ter the successful co-locations in Freiburg (2001), Helsinki (2002), and Cavtat- Dubrovnik (2003), it became clear that researchersstrongly supported the or- nization of a major scienti?c event about machine learning and data mining in Europe. We are happy to provide some statistics about the conferences. 581 di?erent papers were submitted to ECML/PKDD (about a 75% increase over 2003); 280 weresubmittedtoECML2004only,194weresubmittedtoPKDD2004only, and 107weresubmitted to both. Aroundhalfofthe authorsforsubmitted papersare from outside Europe, which is a clear indicator of the increasing attractiveness of ECML/PKDD. The Program Committee members were deeply involved in what turned out to be a highly competitive selection process. We assigned each paper to 3 - viewers, deciding on the appropriate PC for papers submitted to both ECML and PKDD. As a result, ECML PC members reviewed 312 papers and PKDD PC members reviewed 269 papers. We accepted for publication regular papers (45 for ECML 2004 and 39 for PKDD 2004) and short papers that were as- ciated with poster presentations (6 for ECML 2004 and 9 for PKDD 2004). The globalacceptance ratewas14.5%for regular papers(17% if we include the short papers).
Author: Walter Daelemans Publisher: Springer ISBN: 354087481X Category : Computers Languages : en Pages : 721
Book Description
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.
Author: Alípio Jorge Publisher: Springer Science & Business Media ISBN: 3540292446 Category : Computers Languages : en Pages : 738
Book Description
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 qua- ?edindependentreviewsperpaper(withveryfewexceptions)andoneadditional 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. We thank all involved for all the e?ort with reviewing and selection of papers. Besidesthecoretechnicalprogram,ECMLandPKDDhad6invitedspeakers, 10 workshops, 8 tutorials and a Knowledge Discovery Challenge.
Author: Bettina Berendt Publisher: Springer ISBN: 3319461311 Category : Computers Languages : en Pages : 321
Book Description
The three volume set LNAI 9851, LNAI 9852, and LNAI 9853 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2016, held in Riva del Garda, Italy, in September 2016. The 123 full papers and 16 short papers presented were carefully reviewed and selected from a total of 460 submissions. The papers presented focus on practical and real-world studies of machine learning, knowledge discovery, data mining; innovative prototype implementations or mature systems that use machine learning techniques and knowledge discovery processes in a real setting; recent advances at the frontier of machine learning and data mining with other disciplines. Part I and Part II of the proceedings contain the full papers of the contributions presented in the scientific track and abstracts of the scientific plenary talks. Part III contains the full papers of the contributions presented in the industrial track, short papers describing demonstration, the nectar papers, and the abstracts of the industrial plenary talks.
Author: Shichao Zhang
Author: Shichao Zhang
Author: Joao Gama
Author: Khosrow-Pour, D.B.A., Mehdi
Author: Shichao Zhang
Author: Dimitrios Gunopulos
Author: Joost N. Kok
Author: Jean-Francois Boulicaut
Author: Walter Daelemans
Author: Alípio Jorge
Author: Bettina Berendt