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In the simulation results a bias towards syntagmatic associations
Since the associations were computed from co-occurrences of words
in texts, this preference of syntagmatic associations is
not surprising. It is remarkable, instead, that many
associations usually considered to be paradigmatic
are predicted correctly. Examples include man woman,
black white and bitter sweet.
We believe, however, that the tendency to prefer syntagmatic
associations can be reduced by not counting co-occurrences found
within collocations. Equivalently, the association strength between
word pairs always occuring together in a strict formation
(separated by a constant number of other words) could be reduced.
When going from English to German, the parameters and
in equation 6 needed to be readjusted in such a way, that
less frequent words obtained a better chance to be associated.
This reflects the fact, that there is more variation in the
associative responses of German than of American subjects, and
that American subjects tend to respond with words of higher corpus
frequency. We believe that by considering additional languages this
parameter adjustment could be predicted from word-frequency-distribution.
In conclusion, the results show, that free word associations for English and
German can be successfully predicted by an almost identical algorithm
which is based on the co-occurrence-frequencies of words in texts.
Some peculiarities in the associative behavior of the subjects
were confirmed in the simulation.
Together, this is a good indication that the learning of word
associations is governed by the law of association by contiguity.
Although our simulation results are not perfect, specialized
versions of our program have already proved useful in a number of applications:
- Information Retrieval: Generation of search terms for document retrieval in bibliographic databases (Wettler & Rapp, 1989, Ferber,
Wettler & Rapp, 1993).
- Marketing: Association norms are useful to predict what
effects word usage in advertisements has on people (Wettler & Rapp, 1993). Multilingual assocation norms help to find a global
marketing strategy in international markets (Kroeber-Riel,
- Machine Translation: In an experimental prototype we
have shown that associations derived from context are useful to
find the correct translations for semantically ambiguous words.
The successful prediction of different types of verbal behavior on the
basis of co-occurrences of words in texts is a direct application of the
classical contiguity-theory, or, in more modern neurophysiological terms,
of Hebb's learning rule. Cognitive psychology has severely criticized
contiguity-theory with the arguments that association theory did not
produce useful results (Jenkins, 1974), and that associations are not
the result of associative learning but of underlying semantic processes
(Clark, 1970). Both arguments need a critical revision. Recent work with
large corpora as well as a large number of connectionist studies have yielded
very useful results in different psychological domains, and the high
predictive power of the associationist approach makes that the intuitive
appeal of cognitivist explanations is fading rapidly.
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New horizons in linguistics. Harmondsworth: Penguin, 271-286.
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Parsing, word associations and typical predicate-argument relations.
In: Proceedings of the International Workshop on Parsing Technologies,
Carnegie Mellon University, PA, 389-398.
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mutual information, and lexicography. Computational Linguistics,
Volume 16, Number 1, March 1990, 22-29.
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model of word selection in the generation of search queries.
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are worse than none. DARPA Speech and Natural Language Workshop,
Hidden Valley, PA, June 1990, 283-287.
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In: Postman, L., Keppel, G. (eds.): Norms of word association.
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insanity. American Journal of Insanity, 67 (1910), 37-96, 317-390.
- Kroeber-Riel, W. (1992). Globalisierung der Euro-Werbung.
Marketing ZFP, Heft 4, IV Quartal, 261-267.
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associations based on Hebbian learning. Proceedings of the
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das Erinnern von Worten in der deutschen, französischen und englischen
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simulate lexical decisions in information retrieval. In: Pfeifer, R.,
Schreter, Z., Fogelman, F. Steels, L. (eds.), Connectionism in perspective.
Amsterdam: Elsevier, 463-469.
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advertisements. Submitted to Marketing and Research Today.
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