The difficulties involved in spelling error detection and correction in a language have been investigated in this work through the conceptualization of SpellNet – the weighted network of words, where edges indicate orthographic proximity between two words. We construct SpellNets for three languages - Bengali, English and Hindi. Through appropriate mathematical analysis and/or intuitive justification, we interpret the different topological metrics of SpellNet from the perspective of the issues related to spell-checking. We make many interesting observations, the most significant among them being that the probability of making a real word error in a language is propotionate to the average weighted degree of SpellNet, which is found to be highest for Hindi, followed by Bengali and English.

In  Proceedings of HLT-NAACL Workshop - TextGraphs 2

Publisher  Association for Computational Linguistics
All copyrights reserved by ACL 2007

Details