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The first textbook ever to cover multi-relational data mining and inductive logic programming, this book fully explores logical and relational learning. Ideal for graduate students and researchers, it also looks at statistical relational learning. Series: Cognitive Technologies. Num Pages: 402 pages, 10 black & white tables, biography. BIC Classification: UM; UN. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 25. Weight in Grams: 816. . 2008. 2008th Edition. hardcover. . . . . Books ship from the US and Ireland. Codice articolo V9783540200406
This first textbook on multi-relational data mining and inductive logic programming provides a complete overview of the field. It is self-contained and easily accessible for graduate students and practitioners of data mining and machine learning.
Dalla quarta di copertina:
This textbook covers logical and relational learning in depth, and hence provides an introduction to inductive logic programming (ILP), multirelational data mining (MRDM) and (statistical) relational learning (SRL). These subfields of data mining and machine learning are concerned with the analysis of complex and structured data sets that arise in numerous applications, such as bio- and chemoinformatics, network analysis, Web mining, natural language processing, within the rich representations offered by relational databases and computational logic.
The author introduces the machine learning and representational foundations of the field and explains some important techniques in detail by using some of the classic case studies centered around well-known logical and relational systems.
The book is suitable for use in graduate courses and should be of interest to graduate students and researchers in computer science, databases and artificial intelligence, as well as practitioners of data mining and machine learning. It contains numerous figures and exercises, and slides are available for many chapters.
Titolo: Logical and Relational Learning
Casa editrice: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Data di pubblicazione: 2008
Legatura: Rilegato
Condizione: New
Da: Buchpark, Trebbin, Germania
Condizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher. Codice articolo 1755275/1
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Da: moluna, Greven, Germania
Gebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. First textbook on multirelational data mining and inductive logic programming This first textbook on multi-relational data mining and inductive logic programming provides a complete overview of the field. It is self-contained and e. Codice articolo 4884424
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This first textbook on multi-relational data mining and inductive logic programming provides a complete overview of the field. It is self-contained and easily accessible for graduate students and practitioners of data mining and machine learning. 404 pp. Englisch. Codice articolo 9783540200406
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Buch. Condizione: Neu. Neuware -Iusethetermlogicalandrelationallearning torefertothesub eldofarti cial intelligence,machinelearninganddataminingthatisconcernedwithlearning in expressive logical or relational representations. It is the union of inductive logic programming, (statistical) relational learning and multi-relational data mining, which all have contributed techniques for learning from data in re- tional form. Even though some early contributions to logical and relational learning are about forty years old now, it was only with the advent of - ductive logic programming in the early 1990s that the eld became popular. Whereas initial work was often concerned with logical (or logic programming) issues,thefocushasrapidlychangedtothediscoveryofnewandinterpretable knowledge from structured data, often in the form of rules, and soon imp- tant successes in applications in domains such as bio- and chemo-informatics and computational linguistics were realized. Today, the challenges and opp- tunities of dealing with structured data and knowledge have been taken up by the arti cial intelligence community at large and form the motivation for a lot of ongoing research. Indeed, graph, network and multi-relational data mining are now popular themes in data mining, and statistical relational learning is receiving a lot of attention in the machine learning and uncertainty in art- cial intelligence communities. In addition, the range of tasks for which logical and relational techniques have been developed now covers almost all machine learning and data mining tasks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 404 pp. Englisch. Codice articolo 9783540200406
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Da: AHA-BUCH GmbH, Einbeck, Germania
Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Iusethetermlogicalandrelationallearning torefertothesub eldofarti cial intelligence,machinelearninganddataminingthatisconcernedwithlearning in expressive logical or relational representations. It is the union of inductive logic programming, (statistical) relational learning and multi-relational data mining, which all have contributed techniques for learning from data in re- tional form. Even though some early contributions to logical and relational learning are about forty years old now, it was only with the advent of - ductive logic programming in the early 1990s that the eld became popular. Whereas initial work was often concerned with logical (or logic programming) issues,thefocushasrapidlychangedtothediscoveryofnewandinterpretable knowledge from structured data, often in the form of rules, and soon imp- tant successes in applications in domains such as bio- and chemo-informatics and computational linguistics were realized. Today, the challenges and opp- tunities of dealing with structured data and knowledge have been taken up by the arti cial intelligence community at large and form the motivation for a lot of ongoing research. Indeed, graph, network and multi-relational data mining are now popular themes in data mining, and statistical relational learning is receiving a lot of attention in the machine learning and uncertainty in art- cial intelligence communities. In addition, the range of tasks for which logical and relational techniques have been developed now covers almost all machine learning and data mining tasks. Codice articolo 9783540200406
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Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Condizione: New. Codice articolo ABLIING23Mar3113020162339
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. This book constitutes the first textbook on inductive logic programming (ILP) and multi-relational data mining (MRDM). These subfields of data mining and machine learning are concerned with analyzing structured data that arise in numerous applications, such as bioinformatics, web mining, natural language processing, etc. The book explains some important techniques in detail by using case studies centered around well-known ILP or MRDM systems. These case studies are some of the "classics" of the field and also provide an adequate starting point for a more general discussion. Related systems and techniques are covered in a bibliographical section at the end of each chapter.The book addresses graduate students in computer science, data bases and artificial intelligence as well as practitioners of data mining and machine learning. Indeed, graph, network and multi-relational data mining are now popular themes in data mining, and statistical relational learning is receiving a lot of attention in the machine learning and uncertainty in art- cial intelligence communities. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9783540200406
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Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Hardback or Cased Book. Condizione: New. Logical and Relational Learning. Book. Codice articolo BBS-9783540200406
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Da: California Books, Miami, FL, U.S.A.
Condizione: New. Codice articolo I-9783540200406
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