Speller performance prediction for query autocorrection

Authors:
Alexey Baytin;Irina Galinskaya;Marina Panina;Pavel Serdyukov
Affiliations:
Yandex, Moscow, Russian Fed.;Yandex, Moscow, Russian Fed.;Yandex, Moscow, Russian Fed.;Yandex, Moscow, Russian Fed.
Venue:
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Year:
2013

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Abstract

Query speller is an indispensable part of any modern search engine. In this paper we define the problem of speller performance prediction and apply it to the task of query spelling autocorrection. As candidates for query autocorrection we used the suggestions generated by a query speller. To determine their reliability we used a binary classifier trained on manually labeled data. In addition to the basic standard lexical and statistical features we utilized a number of new click-based features, what allowed to significantly outperform the algorithm trained on the basic set of features.