Markov Logic
Title | Markov Logic PDF eBook |
Author | Pedro Dechter |
Publisher | Springer Nature |
Pages | 145 |
Release | 2022-05-31 |
Genre | Computers |
ISBN | 3031015495 |
Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in networking, the relational model in databases, etc.). So far this interface layer has been missing in AI. First-order logic and probabilistic graphical models each have some of the necessary features, but a viable interface layer requires combining both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as templates for features of Markov random fields. Most statistical models in wide use are special cases of Markov logic, and first-order logic is its infinite-weight limit. Inference algorithms for Markov logic combine ideas from satisfiability, Markov chain Monte Carlo, belief propagation, and resolution. Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming. Markov logic has been successfully applied to problems in information extraction and integration, natural language processing, robot mapping, social networks, computational biology, and others, and is the basis of the open-source Alchemy system. Table of Contents: Introduction / Markov Logic / Inference / Learning / Extensions / Applications / Conclusion
ECAI 2008
Title | ECAI 2008 PDF eBook |
Author | European Coordinating Committee for Artificial Intelligence |
Publisher | IOS Press |
Pages | 972 |
Release | 2008 |
Genre | Computers |
ISBN | 1586038915 |
Includes subconference "Prestigious Applications of Intelligent Systems (PAIS 2008)."
Markov Logic
Title | Markov Logic PDF eBook |
Author | Pedro Domingos |
Publisher | Morgan & Claypool Publishers |
Pages | 156 |
Release | 2009-05-08 |
Genre | Computers |
ISBN | 1598296949 |
Most subfields of computer science have an interface layer via which applications communicate with the infrastructure, and this is key to their success (e.g., the Internet in networking, the relational model in databases, etc.). So far this interface layer has been missing in AI. First-order logic and probabilistic graphical models each have some of the necessary features, but a viable interface layer requires combining both. Markov logic is a powerful new language that accomplishes this by attaching weights to first-order formulas and treating them as templates for features of Markov random fields. Most statistical models in wide use are special cases of Markov logic, and first-order logic is its infinite-weight limit. Inference algorithms for Markov logic combine ideas from satisfiability, Markov chain Monte Carlo, belief propagation, and resolution. Learning algorithms make use of conditional likelihood, convex optimization, and inductive logic programming. Markov logic has been successfully applied to problems in information extraction and integration, natural language processing, robot mapping, social networks, computational biology, and others, and is the basis of the open-source Alchemy system.
Probabilistic Inductive Logic Programming
Title | Probabilistic Inductive Logic Programming PDF eBook |
Author | Luc De Raedt |
Publisher | Springer |
Pages | 348 |
Release | 2008-02-26 |
Genre | Computers |
ISBN | 354078652X |
This book provides an introduction to probabilistic inductive logic programming. It places emphasis on the methods based on logic programming principles and covers formalisms and systems, implementations and applications, as well as theory.
Information Retrieval Technology
Title | Information Retrieval Technology PDF eBook |
Author | Hang Li |
Publisher | Springer Science & Business Media |
Pages | 701 |
Release | 2008-05-29 |
Genre | Computers |
ISBN | 3540686339 |
This book constitutes the thoroughly refereed post-conference proceedings of the 4th Asia Information Retrieval Symposium, AIRS 2008, held in Harbin, China, in May 2008. The 39 revised full papers and 43 revised poster papers presented were carefully reviewed and selected from 144 submissions. All current issues in information retrieval are addressed: applications, systems, technologies and theoretical aspects of information retrieval in text, audio, image, video and multi-media data. The papers are organized in topical sections on IR models image retrieval, text classification, chinese language processing, text processing, application of IR, machine learning, taxonomy, IR methods, information extraction, summarization, multimedia, Web IR, and text clustering.
Title | PDF eBook |
Author | |
Publisher | IOS Press |
Pages | 3525 |
Release | |
Genre | |
ISBN |
KI 2007: Advances in Artificial Intelligence
Title | KI 2007: Advances in Artificial Intelligence PDF eBook |
Author | Joachim Hertzberg |
Publisher | Springer Science & Business Media |
Pages | 525 |
Release | 2007-08-30 |
Genre | Computers |
ISBN | 3540745645 |
This book constitutes the thoroughly refereed proceedings of the 30th Annual German Conference on Artificial Intelligence, KI 2007, held in Osnabrück, Germany, September 2007. The papers are organized in topical sections on cognition and emotion, semantic Web, analogy, natural language, reasoning, ontologies, spatio-temporal reasoning, machine learning, spatial reasoning, robot learning, classical AI problems, and agents.