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.

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Paper Submission Open For October 2024
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Last date for paper submission 30th October, 2024
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