Short text clustering using numerical data based on n-gram

Short text messages, especially mobile SMSs contain not only pure textual strings but also contain numeric values. Existing systems discard and filter out these numeric values. In our research, a new approach has been developed which makes usage of numeric values for feature extraction in the process of clustering. We are proposing an algorithm that uses n-gram approach to retrieve the pre-strings and post-strings of each numeric data and then similarity between documents is calculated. Partitioning is done to separate out two types of documents such as pure textual as well as mixed documents. Text messaging is gaining popularity in the field of pushing and providing short indication and informative notifications to users at any time. Use of numerical values through n-gram plays an important role for efficient clustering of text messages.