Topic Quarrying Over Same Time Period Text Documents

Abstract: Texts are spread over in different database having different timestamps. Text share common topics and thus related with each other. They are correlated with respect to the content they have. The content of text may be related with each other with common topics but have different time stamp. The interaction between common topics may derive valuable information but they may not be arranged in indexed fashion as they differ in timestamp. The main goal of this paper is to extract common topic mining with the help of generative model using exact timestamp. It will perform two main operations alternatively. Common topic extraction with adjusted timestamp and next is adjusting the time stamp according to time distribution of the common topics generated previously. These steps will work alternatively and extract the information of common topics.

Keywords: Timestamp, Asynchronous Sequences, Topic mining, Text mining, Correlation.