Author: Sandra Kübler, Eberhard Karls Universität Tübingen
Hardback: ISBN: 1588115909 Pages: viii, 294 pp. Price: U.S. $ 138.00
Hardback: ISBN: 9027249911 Pages: viii, 294 pp. Price: Europe EURO 115.00
Abstract:
Memory-Based Learning (MBL), one of the most influential machine learning
paradigms, has been applied with great success to a variety of NLP tasks.
This monograph describes the application of MBL to robust parsing. Robust
parsing using MBL can provide added functionality for key NLP applications,
such as Information Retrieval, Information Extraction, and Question
Answering, by facilitating more complex syntactic analysis than is
currently available. The text presupposes no prior knowledge of MBL. It
provides a comprehensive introduction to the framework and goes on to
describe and compare applications of MBL to parsing. Since parsing is not
easily characterizable as a classification task, adaptations of standard
MBL are necessary. These adaptations can either take the form of a cascade
of local classifiers or of a holistic approach for selecting a complete tree.
The text provides excellent course material on MBL. It is equally relevant
for any researcher concerned with symbolic machine learning, Information
Retrieval, Information Extraction, and Question Answering.
Linguistic Field(s):
Computational Linguistics
Natural Language Processing
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