Regularized Latent Semantic Indexing: A New Approach to Large-Scale Topic Modeling

@article{Wang2013RegularizedLS,
  title={Regularized Latent Semantic Indexing: A New Approach to Large-Scale Topic Modeling},
  author={Quan Wang and Jun Xu and Hang Li and Nick Craswell},
  journal={ACM Trans. Inf. Syst.},
  year={2013},
  volume={31},
  pages={5:1-5:44}
}
Topic modeling provides a powerful way to analyze the content of a collection of documents. It has become a popular tool in many research areas, such as text mining, information retrieval, natural language processing, and other related fields. In real-world applications, however, the usefulness of topic modeling is limited due to scalability issues. Scaling to larger document collections via parallelization is an active area of research, but most solutions require drastic steps, such as vastly… CONTINUE READING
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