Latest Advances in Inductive Logic Programming

Written By Stephen H Muggleton
Latest Advances in Inductive Logic Programming
  • Publsiher : World Scientific
  • Release : 30 October 2014
  • ISBN : 1783265108
  • Pages : 264 pages
  • Rating : /5 from reviews
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Download or read book entitled Latest Advances in Inductive Logic Programming by author: Stephen H Muggleton which was release on 30 October 2014 and published by World Scientific with total page 264 pages . This book available in PDF, EPUB and Kindle Format. This book represents a selection of papers presented at the Inductive Logic Programming (ILP) workshop held at Cumberland Lodge, Great Windsor Park. The collection marks two decades since the first ILP workshop in 1991. During this period the area has developed into the main forum for work on logic-based machine learning. The chapters cover a wide variety of topics, ranging from theory and ILP implementations to state-of-the-art applications in real-world domains. The international contributors represent leaders in the field from prestigious institutions in Europe, North America and Asia. Graduate students and researchers in this field will find this book highly useful as it provides an up-to-date insight into the key sub-areas of implementation and theory of ILP. For academics and researchers in the field of artificial intelligence and natural sciences, the book demonstrates how ILP is being used in areas as diverse as the learning of game strategies, robotics, natural language understanding, query search, drug design and protein modelling. Contents:Applications:Can ILP Learn Complete and Correct Game Strategies? (Stephen H Muggleton and Changze Xu)Induction in Nonmonotonic Causal Theories for a Domestic Service Robot (Jianmin Ji and Xiaoping Chen)Using Ontologies in Semantic Data Mining with g-SEGS and Aleph (Anže Vavpetič and Nada Lavră)Improving Search Engine Query Expansion Techniques with ILP (José Carlos Almeida Santos and Manuel Fonseca de Sam Bento Ribeiro)ILP for Cosmetic Product Selection (Hiroyuki Nishiyama and Fumio Mizoguchi)Learning User Behaviours in Real Mobile Domains (Andreas Markitanis, Domenico Corapi, Alessandra Russo and Emil C Lupu)Discovering Ligands for TRP Ion Channels Using Formal Concept Analysis (Mahito Sugiyama, Kentaro Imajo, Keisuke Otaki and Akihiro Yamamoto)Predictive Learning in Two-Way Datasets (Beau Piccart, Hendrik Blockeel, Andy Georges and Lieven Eeckhout)Model of Double-Strand Break of DNA in Logic-Based Hypothesis Finding (Barthelemy Dworkin, Andrei Doncescu, Jean-Charles Faye and Katsumi Inoue)Probabilistic Logical Learning:The PITA System for Logical-Probabilistic Inference (Fabrizio Riguzzi and Terrance Swift)Learning a Generative Failure-Free PRISM Clause (Waleed Alsanie and James Cussens)Statistical Relational Learning of Object Affordances for Robotic Manipulation (Bogdan Moldovan, Martijn van Otterlo, Plinio Moreno, José Santos-Victor and Luc De Raedt)Learning from Linked Data by Markov Logic (Man Zhu and Zhiqiang Gao)Satisfiability Machines (Filip Železný)Implementations:Customisable Multi-Processor Acceleration of Inductive Logic Programming (Andreas K Fidjeland, Wayne Luk and Stephen H Muggleton)Multivalue Learning in ILP (Orlando Muoz Texzocotetla and Ren Mac Kinney Romero)Learning Dependent-Concepts in ILP: Application to Model-Driven Data Warehouses (Moez Essaidi, Aomar Osmani and Céline Rouveirol)Graph Contraction Pattern Matching for Graphs of Bounded Treewidth (Takashi Yamada and Takayoshi Shoudai)mLynx: Relational Mutual Information (Nicola Di Mauro, Teresa M A Basile, Stefano Ferilli and Floriana Esposito)Theory:Machine Learning Coalgebraic Proofs (Ekaterina Komendantskaya)Can ILP Deal with Incomplete and Vague Structured Knowledge? (Francesca A Lisi and Umberto Straccia)Logical Learning:Towards Efficient Higher-Order Logic Learning in a First-Order Datalog Framework (Niels Pahlavi and Stephen H Muggleton)Automatic Invention of Functional Abstractions (Robert J Henderson and Stephen H Muggleton)Constraints:Using Machine-Generated Soft Constraints for Roster Problems (Yoshihisa Shiina and Hayato Ohwada)Spatial and Temporal:Relational Learning for Football-Related Predictions (Jan Van Haaren and Guy Van den Broeck) Readership: Graduate students and researchers in the field of ILP, and academics and researchers in the fields of artificial intelligence and natural sciences. Key Features:Covers major areas of research in ILPProvides an up-to-date insight into the key sub-areas of implementation and theory of ILPThe papers in this volume do not appear in conference proceedings elsewhere in the literatureKeywords:Machine Learning;Logic Programs;Inductive Inference;Structure Learning;Relational Learning;Statistical Relational Learning

Latest Advances in Inductive Logic Programming

Latest Advances in Inductive Logic Programming
  • Author : Stephen H Muggleton,Hiroaki Watanabe
  • Publisher : World Scientific
  • Release Date : 2014-10-30
  • Total pages : 264
  • ISBN : 1783265108
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Summary : This book represents a selection of papers presented at the Inductive Logic Programming (ILP) workshop held at Cumberland Lodge, Great Windsor Park. The collection marks two decades since the first ILP workshop in 1991. During this period the area has developed into the main forum for work on logic-based machine learning. ...

Advances in Inductive Logic Programming

Advances in Inductive Logic Programming
  • Author : Luc de Raedt
  • Publisher : Ios PressInc
  • Release Date : 1996
  • Total pages : 323
  • ISBN : 1783265108
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Summary : Inductive Logic Programming is a research area situated in machine learning and logic programming, two subfields of artificial intelligence. The goal of inductive logic programming is to develop theories, techniques and tools for inducing hypotheses from observations using the representations from computational logic. Inductive Logic Programming has a high potential ...

Latest Advances in Inductive Logic Programming

Latest Advances in Inductive Logic Programming
  • Author : Stephen Muggleton,Hiroaki Watanabe
  • Publisher : Unknown
  • Release Date : 2014
  • Total pages : 212
  • ISBN : 1783265108
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Summary : Read online Latest Advances in Inductive Logic Programming written by Stephen Muggleton,Hiroaki Watanabe, published by which was released on 2014. Download full Latest Advances in Inductive Logic Programming Books now! Available in PDF, ePub and Kindle....

Advances in Inductive Logic Programming

Advances in Inductive Logic Programming
  • Author : L. De_Raedt
  • Publisher : Unknown
  • Release Date : 1996
  • Total pages : 323
  • ISBN : 1783265108
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Summary : Read online Advances in Inductive Logic Programming written by L. De_Raedt, published by which was released on 1996. Download full Advances in Inductive Logic Programming Books now! Available in PDF, ePub and Kindle....

Inductive Logic Programming

Inductive Logic Programming
  • Author : James Cussens,Alessandra Russo
  • Publisher : Springer
  • Release Date : 2017-07-15
  • Total pages : 133
  • ISBN : 1783265108
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Summary : This book constitutes the thoroughly refereed post-conference proceedings of the 26th International Conference on Inductive Logic Programming, ILP 2016, held in London, UK, in September 2016. The 10 full papers presented were carefully reviewed and selected from 29 submissions. The papers represent well the current breath of ILP research topics such as predicate invention; ...

Data Mining in Finance

Data Mining in Finance
  • Author : Boris Kovalerchuk,Evgenii Vityaev
  • Publisher : Springer Science & Business Media
  • Release Date : 2006-04-18
  • Total pages : 308
  • ISBN : 1783265108
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Summary : Data Mining in Finance presents a comprehensive overview of major algorithmic approaches to predictive data mining, including statistical, neural networks, ruled-based, decision-tree, and fuzzy-logic methods, and then examines the suitability of these approaches to financial data mining. The book focuses specifically on relational data mining (RDM), which is a learning ...

Inductive Logic Programming

Inductive Logic Programming
  • Author : Nada Lavrač,Sašo Džeroski
  • Publisher : Prentice Hall
  • Release Date : 1994
  • Total pages : 293
  • ISBN : 1783265108
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Summary : Read online Inductive Logic Programming written by Nada Lavrač,Sašo Džeroski, published by Prentice Hall which was released on 1994. Download full Inductive Logic Programming Books now! Available in PDF, ePub and Kindle....

Advances in Knowledge Discovery and Management

Advances in Knowledge Discovery and Management
  • Author : Bruno Pinaud,Fabrice Guillet,Fabien Gandon,Christine Largeron
  • Publisher : Springer
  • Release Date : 2019-06-20
  • Total pages : 183
  • ISBN : 1783265108
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Summary : This book highlights novel research in Knowledge Discovery and Management (KDM), gathering the extended, peer-reviewed versions of outstanding papers presented at the annual conferences EGC’2017 & EGC’2018. The EGC conference cycle was founded by the International French-speaking EGC society (“Extraction et Gestion des Connaissances”) in 2003, and has since become a respected ...

Recent Advances in Robot Learning

Recent Advances in Robot Learning
  • Author : Judy A. Franklin,Tom M. Mitchell,Sebastian Thrun
  • Publisher : Springer Science & Business Media
  • Release Date : 2012-12-06
  • Total pages : 218
  • ISBN : 1783265108
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Summary : Recent Advances in Robot Learning contains seven papers on robot learning written by leading researchers in the field. As the selection of papers illustrates, the field of robot learning is both active and diverse. A variety of machine learning methods, ranging from inductive logic programming to reinforcement learning, is being ...

Enhancing Software Fault Prediction With Machine Learning Emerging Research and Opportunities

Enhancing Software Fault Prediction With Machine Learning  Emerging Research and Opportunities
  • Author : Rashid, Ekbal
  • Publisher : IGI Global
  • Release Date : 2017-09-13
  • Total pages : 129
  • ISBN : 1783265108
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Summary : Software development and design is an intricate and complex process that requires a multitude of steps to ultimately create a quality product. One crucial aspect of this process is minimizing potential errors through software fault prediction. Enhancing Software Fault Prediction With Machine Learning: Emerging Research and Opportunities is an innovative ...

AI IA 2003 Advances in Artificial Intelligence

AI IA 2003  Advances in Artificial Intelligence
  • Author : Italian association for artificial intelligence,Associazione italiana per l'intelligenza artificiale. Congress,Amedeo Cappelli,Franco Turini
  • Publisher : Springer Science & Business Media
  • Release Date : 2003-09-24
  • Total pages : 552
  • ISBN : 1783265108
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Summary : This book constitutes the refereed proceedings of the 8th Congress of the Italian Association for Artificial Intelligence, AI*IA 2003, held in Pisa, Italy in September 2003. The 44 revised full papers presented were carefully reviewed and selected from 91 submissions. The papers are organized in topical sections on knowledge representation and reasoning, soft ...

Advances in Ubiquitous User Modelling

Advances in Ubiquitous User Modelling
  • Author : Tsvi Kuflik,Shlomo Berkovsky,Francesca Carmagnola,Dominikus Heckmann,Antonio Krüger
  • Publisher : Springer
  • Release Date : 2009-10-13
  • Total pages : 159
  • ISBN : 1783265108
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Summary : Ubiquitous user modeling differs from generic user modeling by three additional concepts: ongoing modeling, ongoing sharing, and ongoing exploitation. Systems that share their user models will improve the coverage, the level of detail, and the reliability of the integrated user models and thus allow better functions of adaptation. Ubiquitous user ...

Proceedings of the Annual ACM Conference on Computational Learning Theory

Proceedings of the     Annual ACM Conference on Computational Learning Theory
  • Author : Anonim
  • Publisher : Unknown
  • Release Date : 1997
  • Total pages : 212
  • ISBN : 1783265108
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Summary : Read online Proceedings of the Annual ACM Conference on Computational Learning Theory written by , published by which was released on 1997. Download full Proceedings of the Annual ACM Conference on Computational Learning Theory Books now! Available in PDF, ePub and Kindle....

Representation Learning

Representation Learning
  • Author : Nada Lavrač,Vid Podpečan,Marko Robnik-Šikonja
  • Publisher : Springer
  • Release Date : 2021-08-10
  • Total pages : 163
  • ISBN : 1783265108
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Summary : 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 ...

Perspectives on Ontology Learning

Perspectives on Ontology Learning
  • Author : J. Lehmann,J. Völker
  • Publisher : IOS Press
  • Release Date : 2014-04-03
  • Total pages : 300
  • ISBN : 1783265108
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Summary : Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning. Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume ...