Title :
Sentence completion task using web-scale data
Author :
Kyusong Lee ; Lee, Gwo Giun
Author_Institution :
Dept. of Comput. Sci. & Eng., Pohang Univ. of Sci. & Technol., Pohang, South Korea
Abstract :
We propose a method to automatically answer SAT-style sentence completion questions using web-scale data. Web-scale da-ta have been used in many language studies and have been found to be a very useful resource for improving accuracy in sentence completion task. Our method employs assorted N-gram probability information for each candidate word. We also proposed back-off strategy was used to remove zero probabilities. We found that the accuracy of our proposed method improved by 52-87% over the current state-of-the-art.
Keywords :
natural language processing; probability; SAT-style sentence completion questions; Web-scale data; assorted N-gram probability information; back-off strategy; sentence completion task; zero probability removal; Accuracy; Google; Mathematical model; Pain; Probability; Semantics; Smoothing methods; Lexical Disambiguation; N-gram; Web-cale Data; sentence completion;
Conference_Titel :
Big Data and Smart Computing (BIGCOMP), 2014 International Conference on
Conference_Location :
Bangkok
DOI :
10.1109/BIGCOMP.2014.6741431