Ad-hoc Information Retrieval based on Boosted Latent Dirichlet Allocated Topics

Pablo Ormeno
Pablo Ormeno

2018 37th International Conference of the Chilean Computer Science Society (SCCC), pp. 1-7, 2018.

Cited by: 0|Bibtex|Views83|DOI:https://doi.org/10.1109/SCCC.2018.8705252
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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

Latent Dirichlet Allocation (LDA) is a fundamental method in the text mining field. We propose strategies for topic and model selection based on LDA that exploits the semantic coherence of the topics inferred, boosting the quality of the models found. Then we study how our boosted topic models perform in ad-hoc information retrieval tasks...More

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