Corpus ID: 14505126

Investigating Topic Models for Mobile Short Messaging Service Communication Filtering

@inproceedings{ModupeInvestigatingTM,
  title={Investigating Topic Models for Mobile Short Messaging Service Communication Filtering},
  author={Abiodun Modupe and O. Olugbara}
}
— This research work investigates the use of Latent Dirichlet Allocation (LDA), a generative topic modeling technique to extract latent features arising from mobile Short Messaging Service (SMS) communication for automatic discovery of user interest. This involves integrating temporal ordering of SMS into a generative process in an iterative manner. The mobile SMS documents are partitioned into segments, wherein the discovered topics in each segment are propagated to influence the discovery of… Expand
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