Transactional and Sequential model for pre-processing the textual data

Pre-processing of data in the abstract techniques are by far important and the duration process involved in the flow of information discovery. The convolution pre-processing is determined by the source of data from which we are retrieving. The aim of the paper is to find out how important is pre-processing methods to discover the interesting pattern of user session data and also how to use pre-processing method on mining the textual data. We work on transactional and sequence model for weblog files in text format, text representation and sequence rule analysis is been considered as work model. We make an analysis by comparing four datasets which comprises of different data quality of text and it will be pre-processed in different measures like data will be determined with paragraph sequence, data is determined with sentence sequence, data is determined with paragraph sequence excluding stop words. We utilise the impact of these advanced techniques of pre-processing on both quality and quantity of data measurable in case of paragraph sequence identification.