Poor estimates of context are worse than none
HLT '90 Proceedings of the workshop on Speech and Natural Language
Integrating diverse knowledge sources in text recognition
ACM Transactions on Information Systems (TOIS)
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
Structural ambiguity and lexical relations
Computational Linguistics - Special issue on using large corpora: I
A hybrid approach to adaptive statistical language modeling
HLT '94 Proceedings of the workshop on Human Language Technology
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The relevance of context in disambiguating natural language input has been widely acknowledged in the literature. However, most attempts at formalising the intuitive notion of context tend to treat the word and its context symmetrically. We demonstrate here that traditional measures such as mutual information score are likely to overlook a significant fraction of all co-occurrence phenomena in natural language. We also propose metrics for measuring directed lexical influence and compare performances.