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  • 1
    Book
    Book
    Berlin [u.a.] :Springer,
    UID:
    almafu_BV013346686
    Format: X, 299 S. : graph. Darst.
    ISBN: 3-540-41145-3
    Series Statement: Lecture notes in computer science 1925 : Lecture notes in artificial intelligence
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Logische Programmierung ; Induktion ; Natürliche Sprache ; Sprachverarbeitung ; Computational logic ; Maschinelles Lernen ; Konferenzschrift ; Konferenzschrift ; Kongress ; Konferenzschrift
    URL: Cover
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Book
    Book
    Berlin [u.a.] : Springer
    UID:
    b3kat_BV013346686
    Format: X, 299 S. , graph. Darst.
    ISBN: 3540411453
    Series Statement: Lecture notes in computer science 1925 : Lecture notes in artificial intelligence
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Logische Programmierung ; Induktion ; Natürliche Sprache ; Sprachverarbeitung ; Computational logic ; Maschinelles Lernen ; Konferenzschrift
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    Berlin, Heidelberg : Springer-Verlag Berlin Heidelberg
    UID:
    gbv_1649247354
    Format: Online-Ressource
    ISBN: 9783540400301 , 3540411453
    Series Statement: Lecture Notes in Computer Science 1925
    Content: This book provides a self-contained introduction to Learning Language in Logic (LLL) and, at the same time, competently surveys the current state of the art of research in the area. The book has its origin in the first LLL workshop which took place in Bled, Slovenia in June 1999. Beyond revised workshop papers, a number of additional chapters were solicited from leading researchers in order to achieve complete coverage of all current aspects and to introduce the new area to a broader audience.As the first book devoted to LLL, this thoroughly cross-reviewed state-of-the-art survey will become a valuable source of reference for researchers active in the area. Newcomers or professionals interested in advanced LLL applications will find this book an ideal guide to an exciting new field
    Note: Literaturangaben
    Additional Edition: ISBN 9783540411451
    Additional Edition: Buchausg. u.d.T. Learning language in logic Berlin : Springer, 2000 ISBN 3540411453
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: Logische Programmierung ; Induktion ; Natürliche Sprache ; Sprachverarbeitung ; Computational logic ; Maschinelles Lernen ; Konferenzschrift
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    Online Resource
    Online Resource
    Berlin, Heidelberg :Springer Berlin Heidelberg,
    UID:
    almahu_9947920566402882
    Format: X, 306 p. , online resource.
    ISBN: 9783540400301
    Series Statement: Lecture Notes in Computer Science, 1925
    Content: This volume has its origins in the ?rst Learning Language in Logic (LLL) wo- shop which took place on 30 June 1999 in Bled, Slovenia immediately after the Ninth International Workshop on Inductive Logic Programming (ILP’99) and the Sixteenth International Conference on Machine Learning (ICML’99). LLL is a research area lying at the intersection of computational linguistics, machine learning, and computational logic. As such it is of interest to all those working in these three ?elds. I am pleased to say that the workshop attracted subm- sions from both the natural language processing (NLP) community and the ILP community, re?ecting the essentially multi-disciplinary nature of LLL. Eric Brill and Ray Mooney were invited speakers at the workshop and their contributions to this volume re?ect the topics of their stimulating invited talks. After the workshop authors were given the opportunity to improve their papers, the results of which are contained here. However, this volume also includes a substantial amount of two sorts of additional material. Firstly, since our central aim is to introduce LLL work to the widest possible audience, two introductory chapters have been written. Dzeroski, ? Cussens and Manandhar provide an - troduction to ILP and LLL and Thompson provides an introduction to NLP.
    Note: Introductions & Overviews -- An Introduction to Inductive Logic Programming and Learning Language in Logic -- A Brief Introduction to Natural Language Processing for Non-linguists -- A Closer Look at the Automatic Induction of Linguistic Knowledge -- Learning for Semantic Interpretation: Scaling Up without Dumbing Down -- Morphology & Phonology -- Learning to Lemmatise Slovene Words -- Achievements and Prospects of Learning Word Morphology with Inductive Logic Programming -- Learning the Logic of Simple Phonotactics -- Syntax -- Grammar Induction as Substructural Inductive Logic Programming -- Experiments in Inductive Chart Parsing -- ILP in Part-of-Speech Tagging — An Overview -- Iterative Part-of-Speech Tagging -- DCG Induction Using MDL and Parsed Corpora -- Learning Log-Linear Models on Constraint-Based Grammars for Disambiguation -- Unsupervised Lexical Learning with Categorial Grammars Using the LLL Corpus -- Induction of Recursive Transfer Rules -- Learning for Text Categorization and Information Extraction with ILP -- Corpus-Based Learning of Semantic Relations by the ILP System, Asium -- Improving Learning by Choosing Examples Intelligently in Two Natural Language Tasks.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783540411451
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 5
    Online Resource
    Online Resource
    Berlin, Heidelberg :Springer Berlin Heidelberg :
    UID:
    almahu_9948621648402882
    Format: X, 306 p. , online resource.
    Edition: 1st ed. 2000.
    ISBN: 9783540400301
    Series Statement: Lecture Notes in Artificial Intelligence ; 1925
    Content: This volume has its origins in the ?rst Learning Language in Logic (LLL) wo- shop which took place on 30 June 1999 in Bled, Slovenia immediately after the Ninth International Workshop on Inductive Logic Programming (ILP'99) and the Sixteenth International Conference on Machine Learning (ICML'99). LLL is a research area lying at the intersection of computational linguistics, machine learning, and computational logic. As such it is of interest to all those working in these three ?elds. I am pleased to say that the workshop attracted subm- sions from both the natural language processing (NLP) community and the ILP community, re?ecting the essentially multi-disciplinary nature of LLL. Eric Brill and Ray Mooney were invited speakers at the workshop and their contributions to this volume re?ect the topics of their stimulating invited talks. After the workshop authors were given the opportunity to improve their papers, the results of which are contained here. However, this volume also includes a substantial amount of two sorts of additional material. Firstly, since our central aim is to introduce LLL work to the widest possible audience, two introductory chapters have been written. Dzeroski, ? Cussens and Manandhar provide an - troduction to ILP and LLL and Thompson provides an introduction to NLP.
    Note: Introductions & Overviews -- An Introduction to Inductive Logic Programming and Learning Language in Logic -- A Brief Introduction to Natural Language Processing for Non-linguists -- A Closer Look at the Automatic Induction of Linguistic Knowledge -- Learning for Semantic Interpretation: Scaling Up without Dumbing Down -- Morphology & Phonology -- Learning to Lemmatise Slovene Words -- Achievements and Prospects of Learning Word Morphology with Inductive Logic Programming -- Learning the Logic of Simple Phonotactics -- Syntax -- Grammar Induction as Substructural Inductive Logic Programming -- Experiments in Inductive Chart Parsing -- ILP in Part-of-Speech Tagging - An Overview -- Iterative Part-of-Speech Tagging -- DCG Induction Using MDL and Parsed Corpora -- Learning Log-Linear Models on Constraint-Based Grammars for Disambiguation -- Unsupervised Lexical Learning with Categorial Grammars Using the LLL Corpus -- Induction of Recursive Transfer Rules -- Learning for Text Categorization and Information Extraction with ILP -- Corpus-Based Learning of Semantic Relations by the ILP System, Asium -- Improving Learning by Choosing Examples Intelligently in Two Natural Language Tasks.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783662170731
    Additional Edition: Printed edition: ISBN 9783540411451
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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