Context Dependent Bag of Words Generation

Abstract

Query spelling correction is a crucial component in modern text mining systems such as Question-answering systems and Sentiment Analysis systems where noise can affect the query matching score. In many existing query matching systems Bag of Words (BoW) generation method is used to generate candidates for noisy words. But in these systems candidate generation do not depend upon context of a query sentence. BoW count for each noisy word may vary and selecting correct candidates from such list is not easy and may result in wrong selection. With our context dependent BoW generation method very few but highly probable candidates are generated which are easy for look up and process of query spelling correction would be easier and efficient.