Social Sciences
2 years ago

Uncovering hidden topics in text data revolutionizes information discovery.

2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COM-IT-CON)
Latent Dirichlet Allocation - An approach for topic discovery
Astha Goyal, Indu Kashyap

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Topic Modeling is a method used to uncover hidden themes in large amounts of text. One popular technique within topic modeling is Latent Dirichlet Allocation (LDA), which has evolved into various versions like hLDA and DTM. This approach helps researchers analyze and understand the topics present in a body of text. By using LDA and its advancements, researchers can efficiently process and extract meaningful information from vast amounts of textual data.