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Paper Information

lrec2018-main-134

Candidate Ranking for Maintenance of an Online Dictionary

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Title

Candidate Ranking for Maintenance of an Online Dictionary

Abstract

Traditionally, the process whereby a lexicographer identifies a lexical item to add to a dictionary -- a database of lexical items -- has been time-consuming and subjective. In the modern age of online dictionaries, all queries for lexical entries not currently in the database are indistinguishable from a larger list of misspellings, meaning that potential new or trending entries can get lost easily. In this project, we develop a system that uses machine learning techniques to assign these ``misspells'' a probability of being a novel or missing entry, incorporating signals from orthography, usage by trusted online sources, and dictionary query patterns.


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