Topic dependent cross-word Spelling Corrections for Web Sentiment Analysis | IEEE Conference Publication | IEEE Xplore

Topic dependent cross-word Spelling Corrections for Web Sentiment Analysis


Abstract:

Spelling Correction is a crucial component in modern text mining systems such as Web Sentiment Analysis systems where spelling errors may affect the sentiment scores. Man...Show More

Abstract:

Spelling Correction is a crucial component in modern text mining systems such as Web Sentiment Analysis systems where spelling errors may affect the sentiment scores. Many existing spelling correction methods generally deal with in-word spelling errors. Major drawback with such methods is that they are unable to handle cross-words spelling errors such as splitting and concatenation. In this paper we address this limitation by our discriminative approach that handles splitting and concatenation errors over a particular topic. It also handles the cases where these errors occur over in-word spelling errors.
Date of Conference: 22-25 August 2013
Date Added to IEEE Xplore: 21 October 2013
ISBN Information:
Conference Location: Mysore, India

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