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Artificial Intelligence in Medicine
This book constitutes the refereed proceedings of the 12th Conference on Artificial Intelligence in Medicine in Europe, AIME 2009, held in Verona, Italy in July 2009. The 24 revised long papers and 36 revised short papers presented together with 2 invited talks were carefully reviewed and selected from 140 submissions. The papers are organized in topical sections on agent-based systems, temporal data mining, machine learning and knowledge discovery, text mining, natural language processing and generation, ontologies, decision support systems, applications of AI-based image processing techniques, protocols and guidelines, as well as workflow systems.
Inductive Logic Programming
This book constitutes the thoroughly refereed post-proceedings of the 16th International Conference on Inductive Logic Programming, ILP 2006, held in Santiago de Compostela, Spain, in August 2006. The papers address all current topics in inductive logic programming, ranging from theoretical and methodological issues to advanced applications.
Discovery Science
The LNAI series reports state-of-the-art results in artificial intelligence research, development, and education, at a high level and in both printed and electronic form. Enjoying tight cooperation with the R & D community, with numerous individuals, as well as with prestigious organizations and societies, LNAI has grown into the most comprehensive artificial intelligence research forum available. The scope of LNAI spans the whole range of artificial intelligence and intelligent information processing including interdisciplinary topics in a variety of application fields. The type of material published traditionally includes proceedings (published in time for the respective conference) post-p...
Data Mining
Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations,...
Professional Practice in Artificial Intelligence
The Second Symposium on Professional Practice in AI 2006 is a conference within the IFIP World Computer Congress 2006, Santiago, Chile. The Symposium is organised by the IFIP Technical Committee on Artificial Intelligence (Technical Committee 12) and its Working Group 12.5 (Artificial Intelligence Applications). The First Symposium in this series was one of the conferences in the IFIP World Computer Congi-ess 2004, Toulouse France. The conference featured invited talks by Rose Dieng, John Atkinson, John Debenham and Max Bramer. The Symposium was a component of the IFIP AI 2006 conference, organised by Professor Max Bramer. I should like to thank the Symposium General Chair, Professor Bramer ...
Chinese Identities on Screen
Since 1978, the changes brought on by China's reforms have had an inevitable and significant impact on the development of literature, the arts, and the whole spectrum of culture. As well, contemporary Chinese films have reflected this transition towards commercialization and internationalization, which has included constant changes in cultural policies and the economic conditions for film production. The articles in this collection argue that contemporary Chinese films display a profound shift in identity construction. They explore Chinese identities related to class, nation, and gender, and they highlight aspects of individual identity. All of these are marked by contradiction, tension, multiple versions, changes over time, and other evidence of contingency and construction. The book draws attention to uncertain and unpredictable qualities of "Chineseness" which are often torn between past and present, but are also increasingly comprised of local, national, and global elements. (Series: Chinese History and Society / Berliner China-Hefte - Vol. 40)
Relational Data Mining
As the first book devoted to relational data mining, this coherently written multi-author monograph provides a thorough introduction and systematic overview of the area. The first part introduces the reader to the basics and principles of classical knowledge discovery in databases and inductive logic programming; subsequent chapters by leading experts assess the techniques in relational data mining in a principled and comprehensive way; finally, three chapters deal with advanced applications in various fields and refer the reader to resources for relational data mining. This book will become a valuable source of reference for R&D professionals active in relational data mining. Students as well as IT professionals and ambitioned practitioners interested in learning about relational data mining will appreciate the book as a useful text and gentle introduction to this exciting new field.
Machine Learning and Knowledge Discovery in Databases
This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2010, held in Barcelona, Spain, in September 2010. The 120 revised full papers presented in three volumes, together with 12 demos (out of 24 submitted demos), were carefully reviewed and selected from 658 paper submissions. In addition, 7 ML and 7 DM papers were distinguished by the program chairs on the basis of their exceptional scientific quality and high impact on the field. 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. A topic widely explored from both ML and DM perspectives was graphs, with motivations ranging from molecular chemistry to social networks.
Representation Learning
This monograph addresses advances in representation learning, a cutting-edge research area of machine learning. Representation learning refers to modern data transformation techniques that convert data of different modalities and complexity, including texts, graphs, and relations, into compact tabular representations, which effectively capture their semantic properties and relations. The monograph focuses on (i) propositionalization approaches, established in relational learning and inductive logic programming, and (ii) embedding approaches, which have gained popularity with recent advances in deep learning. The authors establish a unifying perspective on representation learning techniques developed in these various areas of modern data science, enabling the reader to understand the common underlying principles and to gain insight using selected examples and sample Python code. The monograph should be of interest to a wide audience, ranging from data scientists, machine learning researchers and students to developers, software engineers and industrial researchers interested in hands-on AI solutions.
Constraint-Based Mining and Inductive Databases
The interconnected ideas of inductive databases and constraint-based mining are appealing and have the potential to radically change the theory and practice of data mining and knowledge discovery. This book reports on the results of the European IST project "cInQ" (consortium on knowledge discovery by Inductive Queries) and its final workshop entitled Constraint-Based Mining and Inductive Databases organized in Hinterzarten, Germany in March 2004.
