ISSN (Online) : 2456 - 0774

Email : ijasret@gmail.com

ISSN (Online) 2456 - 0774


Time Stamp Based Topic Mining Over TextSequences 

Abstract

Abstract Textare scattered and spread across in different documents with differenttimestamps shared messages, general topics, and other. They have a relationshipwith the content. The content of the message may be related to other documentsof topics, but with different timestamps. Interactions between general topicsmay receive valuable information. However, it may not be prepared in an indexedformat, because there is a difference in time. The main goal of this paper isto isolate common-topic mining with the help of the timestamp generator model,which will of course perform two major tasks. Extraction of general topics fromtext sequences documents by adjusting the time stamps. The timestamp is basedon the time distribution of the general topic created previously. These stepswill work or retrieve general topic information.

Keywords: Text sequences, Topic mining ,Topic model, worddistribution, time distribution.

Full Text PDF

IMPORTANT DATES 

Submit paper at ijasret@gmail.com

Paper Submission Open For March 2024
UGC indexed in (Old UGC) 2017
Last date for paper submission 30th March, 2024
Deadline Submit Paper any time
Publication of Paper Within 01-02 Days after completing all the formalities
Paper Submission Open For Publication /online Conference 
Publication Fees  
Free for PR Students