LEARNING LANGUAGE IN LOGIC (LLL)

Page maintained by James Cussens

Last updated $Date: 2005/06/24 08:31:17 $


[News and Forthcoming Events] [Introduction] [Bibliography] [Datasets] [Courses] [Events] [Special interest groups] [Research groups] [Useful links]


News and Forthcoming Events


Introduction

This page is intended to provide a resource for those interested in Learning Language in Logic (LLL). LLL concerns the application of machine learning to various natural language tasks, where a logical (usually first-order) representation is used. Inductive logic programming (ILP) applied to natural language thus forms a core component of LLL research. The rationale for LLL is that since logic has been found to be such a useful formalism for 'deductive' natural language tasks it merits serious consideration also for 'inductive' tasks. In most LLL work logic is used in tandem with other approaches, most commonly statistical NLP of one sort or another. So hopefully this resource will be useful to anyone for whom logic forms a part of their approach to natural language machine learning.

Picture of LLL book

The Learning Language in Logic book was published by Springer in 2000. It covers the state-of-the-art at that time. (For LLL work right up to the present day go to the LLL bibliography.) Clicking on the image will take you to Springer's page for this book. Some people will have access to full text via this route. The book contains this introductory article: An introduction to inductive logic programming and learning language in logic by Sašo Džeroski, James Cussens, and Suresh Manandhar. A pre-print gzipped PostScript version of this article is available here.


Bibliography


Datasets


Courses


Events


Special interest groups


Research groups


Useful links


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