ISBN: 9783642057489

Iusethetermlogicalandrelationallearning torefertothesub?eldofarti?cial intelligence,machinelearninganddataminingthatisconcernedwithlearning in expressive logical or relational representat… Altro …

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. 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. Buch (fremdspr.) Bücher>Fremdsprachige Bücher>Englische Bücher>Fantasy & Science Fiction, Springer<

2010, ISBN: 9783642057489

Iusethetermlogicalandrelationallearning torefertothesub?eldofarti?cial intelligence,machinelearninganddataminingthatisconcernedwithlearning in expressive logical or relational representat… Altro …

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. Buch (fremdspr.) Luc de Raedt Taschenbuch, Springer Berlin, 12.02.2010, Springer Berlin, 2010<

ISBN: 9783642057489

Paperback, [PU: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG], The first textbook ever to cover multi-relational data mining and inductive logic programming, this book fully explor… Altro …

Paperback, [PU: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG], 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., Computing: General, Operating Systems, Computer Programming / Software Development, Database Programming, Software Engineering, Databases, Data Warehousing, Data Mining, Information Retrieval, Computer Science, Artificial Intelligence, Expert Systems / Knowledge-based Systems<

2010, ISBN: 3642057489

edizione con copertina rigida

Softcover reprint of hardcover 1st ed. 2008 Kartoniert / Broschiert Software Engineering, Datenbanken, Data Warehousing, Data Mining, Informationsrückgewinnung, Information Retrieval, A… Altro …

Softcover reprint of hardcover 1st ed. 2008 Kartoniert / Broschiert Software Engineering, Datenbanken, Data Warehousing, Data Mining, Informationsrückgewinnung, Information Retrieval, Angewandte Informatik, Künstliche Intelligenz, ArtificialIntelligence; datamining; Database; intelligence; machinelearning; programming; relationaldatabase; Webmining, mit Schutzumschlag 11, [PU:Springer Berlin Heidelberg; Springer-Verlag GmbH]<

ISBN: 9783642057489

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 stud… Altro …

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., [PU: Springer, Berlin/Heidelberg/New York, NY]<