Word Association Norms, Mutual Information and Lexicography

@inproceedings{Church1989WordAN,
  title={Word Association Norms, Mutual Information and Lexicography},
  author={Kenneth Ward Church and Patrick Hanks},
  booktitle={ACL},
  year={1989}
}
The term word association is used in a very particular sense in the psycholinguistic literature. (Generally speaking, subjects respond quicker than normal to the word nurse if it follows a highly associated word such as doctor. ) We will extend the term to provide the basis for a statistical description of a variety of interesting linguistic phenomena, ranging from semantic relations of the doctor/nurse type (content word/content word) to lexico-syntactic co-occurrence constraints between verbs… Expand
Exploring the Chinese Mental Lexicon with Word Association Norms
  • O. Kwong
  • Computer Science, Psychology
  • PACLIC
  • 2013
TLDR
The design and implementation of a pilot word association test on native Hong Kong Cantonese speakers reveal interesting properties of the Chinese mental lexicon, such as the dominance of disyllabic and nominal concepts, and collocational associations. Expand
Strong Associations Can Be Weak: Some Thoughts on Cross-lingual Word Webs for Translation
TLDR
It is suggested that although free associations elicited in isolated context serve to reveal a wide range of potential lexical relations, their usefulness and relevance in real language applications should consider the actual task and its information demand. Expand
CLAD: A corpus-derived Chinese Lexical Association Database
TLDR
Comparison of the CLAD with a database of traditional Chinese word association norms shows that word associations extracted from large text corpora are similar in strength to those elicited from free association tests but contain a much greater number of associative word pairs. Expand
Using Word Association Norms to Measure Corpus Representativeness
TLDR
The more representative a corpus is for the language environment of the test persons, the better the associations generated from it should match people's associations, and the similarity between the two is taken as a measure of corpus representativeness. Expand
Lexical Co-occurrence, Statistical Significance, and Word Association
TLDR
A new measure of word association based on a new notion of statistical significance for lexical co-occurrences is proposed, which focuses only on documents that contain both terms and asks if the distribution of the observed spans of the word-pair resembles that under a random null model. Expand
Using Word Familiarities and Word Associations to Measure Corpus Representativeness
The definition of corpus representativeness used here assumes that a representative corpus should reflect as well as possible the average language use a native speaker encounters in everyday lifeExpand
Solving the Polysemy Problem of Persian Words Using Mutual Information Statistics
In recent years, large monolingual, comparable and parallel corpora have played a very crucial role in solving various problems of computational linguistics including machine translation, informationExpand
Experiments in automatic word class and word sense identification for information retrieval
TLDR
The methods described here use a combination of mutual information and word context to establish word similarities and an extension of the method to handle the difficult problems of disambiguation and of determining part-of-speech and semantic information for low-frequency words. Expand
Word Association Norms as a Unique Supplement of Traditional Language Resources
TLDR
Quantitative and qualitative outputs of the research show that WAN can be employed to enrich the traditional LRs and serve as a tool for their consistency checking. Expand
Measuring Collocation Tendency of Words
TLDR
An attempt has been made to extract collocations by measuring collocation tendency of words and word combinations using a method designed to improve current statistical methods that generate ranked lists of collocation candidates. Expand
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Word AssociationNorms." University of Minnesota Press, Minneapolis, MN
  • 1964
Word association norms
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