SOTAVerified

Topic Models

A topic model is a type of statistical model for discovering the abstract "topics" that occur in a collection of documents. Topic modeling is a frequently used text-mining tool for the discovery of hidden semantic structures in a text body.

Papers

Showing 561570 of 881 papers

TitleStatusHype
Learning Multilingual Topics from Incomparable Corpora0
Learning Polylingual Topic Models from Code-Switched Social Media Documents0
Learning Reputation in an Authorship Network0
Learning Semantics and Selectional Preference of Adjective-Noun Pairs0
Learning Supervised Topic Models for Classification and Regression from Crowds0
Learning the Information Divergence0
Learning the Latent Semantics of a Concept from its Definition0
Learning to Extract International Relations from Political Context0
Learning Topic Models and Latent Bayesian Networks Under Expansion Constraints0
Learning Topic Models by Neighborhood Aggregation0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.69Unverified
2GSMC_v0.55Unverified
3vNVDMC_v0.52Unverified
4ETMC_v0.51Unverified
5NSTMC_v0.38Unverified
6ProdLDAC_v0.35Unverified
#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.49Unverified
2vNVDMC_v0.44Unverified
3GSMC_v0.41Unverified
4ETMC_v0.41Unverified
5NSTMC_v0.37Unverified
6ProdLDAC_v0.32Unverified
#ModelMetricClaimedVerifiedStatus
1NVDMTest perplexity836Unverified
2Bayesian SMMTest perplexity515Unverified
#ModelMetricClaimedVerifiedStatus
1JoSHMACC83.24Unverified
2TopicEqTopic Coherence@500.1Unverified
#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.49Unverified
#ModelMetricClaimedVerifiedStatus
1JoSHMACC90.91Unverified