Machine Learning and Knowledge Discovery in Databases

Machine Learning and Knowledge Discovery for Engineering Systems Health Management presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of

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

Knowledge Discovery from Legal Databases is the first text to describe data mining techniques as they apply to law. Law students, legal academics and applied information technology specialists are gui

A state of the art research monograph that develops the specific and increasingly important area of multiple database mining.

Core Insight：Cross-Domain Data Collaboration: Unlocking Chip PotentialEliminating the "efficiency gap" caused by knowledge silos is the starting point for industry potential. Data doesn't lie; Data Science provides the solution: Through innovation and cross-domain restructuring, we visualize results to become the critical accelerator for boosting efficiency.GenAI Reshaping the Future of SemiconductorsFacing the immense challenge of the slowing pace of Moore's Law, the semiconductor industry urgently requires new breakthroughs. This book is specifically designed to solve the "Efficiency Black Hole" that consumes tens of billions of dollars annually in the industry.The Empowering DTCO Innovation with AI and Machine Learning offers readers a practical DTCO.ML Framework, demonstrating how to leverage Machine Learning (ML) and Generative AI (GenAI) technologies to inject new acceleration into chip manufacturing processes. Learn to master process variability and optimize chip energy efficien

This book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection

This book is a collection of representative and novel works done in Data Mining, Knowledge Discovery, Clustering and Classification that were originally presented in French at the EGC'2012 Conference

Machine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and disc

Collecting extended and improved versions of papers presented at the EGC 2011 Conference, this book covers rule and pattern data mining with topological approaches and with OLAP, and also examines use

What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual pro

What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual pro

During the last decade, Knowledge Discovery and Management (KDM or, in French, EGC for Extraction et Gestion des connaissances) has been an intensive and fruitful research topic in the French-speaking

Converting today's onslaught of information into usable knowledge is one of the main challenges facing us in the modern era. This volume covers a wide range of topics, from ontology learning to data m

"This book deals with knowledge discovery and data mining in spatial and temporal data, seeking to present novel methods that can be employed to discover spatial structures and processes in complex da