Analogical Modeling

An exemplar-based approach to language

Editors
| Brigham Young University, Provo, Utah
| Brigham Young University, Provo, Utah
| Brigham Young University, Provo, Utah
HardboundAvailable
ISBN 9789027223623 (Eur) | EUR 125.00
ISBN 9781588113023 (USA) | USD 188.00
 
e-Book
ISBN 9789027296948 | EUR 125.00 | USD 188.00
 
Analogical Modeling (AM) is an exemplar-based general theory of description that uses both neighbors and non-neighbors (under certain well-defined conditions of homogeneity) to predict language behavior. This book provides a basic introduction to AM, compares the theory with nearest-neighbor approaches, and discusses the most recent advances in the theory, including psycholinguistic evidence, applications to specific languages, the problem of categorization, and how AM relates to alternative approaches of language description (such as instance families, neural nets, connectionism, and optimality theory). The book closes with a thorough examination of the problem of the exponential explosion, an inherent difficulty in AM (and in fact all theories of language description). Quantum computing (based on quantum mechanics with its inherent simultaneity and reversibility) provides a precise and natural solution to the exponential explosion in AM. Finally, an extensive appendix provides three tutorials for running the AM computer program (available online).
[Human Cognitive Processing, 10]  2002.  x, 416 pp.
Publishing status: Available
Table of Contents
List of contributors
ix
Introduction
Royal Skousen
1–8
Part I. The basics of Analogical Modeling
1. An overview of Analogical Modeling
Royal Skousen
11–26
2. Issues in Analogical Modeling
Royal Skousen
27–48
Part II. Psycholinguistic evidence for Analogical Modeling
3. Skousen’s analogical approach as an exemplar-based model of categorization
Steve Chandler
51–105
Part III. Applications to specific languages
4. Applying Analogical Modeling to the German plural
Douglas J. Wulf
109–122
5. Testing Analogical Modeling: The /k/~Ø alternation in Turkish
C. Anton Rytting
123–137
Part IV. Comparing Analogical Modeling with TiMBL
6. A comparison of two analogical models: Tilburg Memory-Based Learner versus Analogical Modeling
David Eddington
141–155
7. A comparison of Analogical Modeling to Memory-Based Language Processing
Walter Daelemans
157–179
8. Analogical hierarchy: Exemplar-based modeling of linkers in Dutch noun-noun compounds
Andrea Krott, Robert Schreuder and Harald Baayen
181–206
Part V. Extending Analogical Modeling
9. Expanding k -NN analogy with instance families
Antal van den Bosch
209–223
10. Version spaces, neural networks, and Analogical Modeling
Mike Mudrow
225–264
11. Exemplar-driven analogy in Optimality Theory
James Myers
265–300
12. The hope for analogous categories
Christer Johansson
301–316
Part VI. Quantum computing and the exponential explosion
13. Analogical Modeling and quantum computing
Royal Skousen
319–346
Part VII. Appendix
14. Data files for Analogical Modeling
Deryle Lonsdale
349–363
15. Running the Perl/C version of the Analogical Modeling program
Dilworth B. Parkinson
365–383
16. Implementing the Analogical Modeling algorithm
Theron Stanford
385–409
Index
411–416
“It used to be a cliche that language users produce and understand new utterances on the basis of analogies they construct with previous linguistic experiences. A formal articulation of the notion of analogy was, however, lacking for a long time. Skousen's explicit formulation of analogy has triggered a resurgence of interest in analogy-based language processing. This book does a wonderful job of combining a tutorial on analogical modeling with a state-of-the-art overview of the field. It should be read by all who are interested in the interface between language, cognition, and computation.”
“Analogy — one of the most intuitive but elusive processes in language learning and change is here confronted directly, given a formal implementation and shown to be the force behind rule-like

behavior.”
“The latest word on analogical modeling. This volume clearly distinguishes AM from both connectionism and symbolic rule systems.”
“This book succeeds extremely well in providing the reader with a tutorial on analogical modeling (AM) and the state-of-the art of the field, and is especially interesting for computational linguists.”
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ARNDT-LAPPE, SABINE
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Milin, Petar, Emmanuel Keuleers & Dušica Đurđević
2011. Allomorphic responses in Serbian pseudo-nouns as a result of analogical learning. Acta Linguistica Hungarica 58:1  pp. 65 ff. Crossref logo
Nesset, Tore & Anastasia Makarova
2014. Testing the Semantic Homogeneity Constraint: Analogical change and Russian verbs. Journal of Historical Linguistics 4:2  pp. 161 ff. Crossref logo
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2017.  In Acquiring Sociolinguistic Variation [Studies in Language Variation, 20],  pp. 267 ff. Crossref logo
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2014. Explaining tense marking changes in Swedish verbs: An application of two analogical computer models. Journal of Historical Linguistics 4:2  pp. 192 ff. Crossref logo
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2013. Analogy in the emergence of intrusive-r in English. English Language and Linguistics 17:1  pp. 55 ff. Crossref logo
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This list is based on CrossRef data as of 01 may 2020. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers. Any errors therein should be reported to them.

Subjects
BIC Subject: CF – Linguistics
BISAC Subject: LAN009000 – LANGUAGE ARTS & DISCIPLINES / Linguistics / General
U.S. Library of Congress Control Number:  2002028283