Main Reference PaperWhat and With Whom? Identifying Topics in Twitter Through Both Interactions and Text, IEEE Transactions on Services Computing, April 2017 [R]
  • Topic derivation method based on two-step matrix factorization process is proposed in which several semantic features of the tweets such as retweets, replies, people along with the content of the tweet are used.

Description
  • Topic derivation method based on two-step matrix factorization process is proposed in which several semantic features of the tweets such as retweets, replies, people along with the content of the tweet are used.

  • To derive topic from the tweets with data sparsity.

  • To assist in various tweet applications.

Aim & Objectives
  • To derive topic from the tweets with data sparsity.

  • To assist in various tweet applications.

  • Incorporating temporal features are considered in topic derivation.

Contribution
  • Incorporating temporal features are considered in topic derivation.

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.

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