Topic Digging Over Asynchronous Text Sequences (International Journal of Engineering and Computer Science, 2016)
Nowadays use of internet is growing rapidly. Most of the information share and use by end users on the web. In any format data or information access by user, most of the available information is in text format. All such text documents available have common content between them with different time stamp. The mutual action between common topics may deduce valuable knowledge but as they are not aligned properly they are not arranged in index fashion. The absolute purpose of this paper is to extract common topic with the help of topic model using appropriate time period. Generative topic model follows two alternative steps. First is retrieve common topic from all the documents with their adjusted time stamp and second is adjusting the time stamp with respect to time period dispersion of common topic being formely generated.