TY - GEN
T1 - Context-sensitive malicious spelling error correction
AU - Gong, Hongyu
AU - Li, Yuchen
AU - Bhat, Suma
AU - Viswanath, Pramod
N1 - Funding Information:
This work is supported in part by the IBM-Illinois Center for Cognitive Computing Systems Research (C3SR) - a research collaboration as part of the IBM AI Horizons Network.
Funding Information:
This work is supported in part by the IBM-ILLINOIS Center for Cognitive Computing Systems Research (C3SR) - a research collaboration as part of the IBM AI Horizons Network.
Publisher Copyright:
© 2019 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License.
PY - 2019/5/13
Y1 - 2019/5/13
N2 - Misspelled words of the malicious kind work by changing specific keywords and are intended to thwart existing automated applications for cyber-environment control such as harassing content detection on the Internet and email spam detection. In this paper, we focus on malicious spelling correction, which requires an approach that relies on the context and the surface forms of targeted keywords. In the context of two applications-profanity detection and email spam detection-we show that malicious misspellings seriously degrade their performance. We then propose a context-sensitive approach for malicious spelling correction using word embeddings and demonstrate its superior performance compared to state-of-the-art spell checkers.
AB - Misspelled words of the malicious kind work by changing specific keywords and are intended to thwart existing automated applications for cyber-environment control such as harassing content detection on the Internet and email spam detection. In this paper, we focus on malicious spelling correction, which requires an approach that relies on the context and the surface forms of targeted keywords. In the context of two applications-profanity detection and email spam detection-we show that malicious misspellings seriously degrade their performance. We then propose a context-sensitive approach for malicious spelling correction using word embeddings and demonstrate its superior performance compared to state-of-the-art spell checkers.
KW - Cyberbullying
KW - Machine learning
KW - Malicious spelling correction
UR - http://www.scopus.com/inward/record.url?scp=85066899983&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85066899983&partnerID=8YFLogxK
U2 - 10.1145/3308558.3313431
DO - 10.1145/3308558.3313431
M3 - Conference contribution
AN - SCOPUS:85066899983
T3 - The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019
SP - 2771
EP - 2777
BT - The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019
PB - Association for Computing Machinery, Inc
T2 - 2019 World Wide Web Conference, WWW 2019
Y2 - 13 May 2019 through 17 May 2019
ER -