• Journal of Advanced Marine Engineering and Technology
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• v.39 no.6
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• pp.656-661
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• 2015

The goal of this paper is to analyze the performance of a word autocomplete system for mobile devices such as smartphones, tablets, and PCs. The proposed system automatically completes a partially typed string into a full word, reducing the time and effort required by a user to enter text on these devices. We collect a large amount of data from Twitter and develop both unigram and bigram dictionaries based on the frequency of words. Using these dictionaries, we analyze the performance of the word autocomplete system and devise a keystroke profit rate and recovery rate as new evaluation metrics that better describe the characteristics of the word autocomplete problem compared to previous measures such as the mean reciprocal rank or recall.