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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 426–450 of 881 papers

TitleStatusHype
Evaluation of Non-Negative Matrix Factorization and n-stage Latent Dirichlet Allocation for Emotion Analysis in Turkish Tweets—0
Evolutionary Hierarchical Dirichlet Process for Timeline Summarization—0
Evolution of topics in central bank speech communication—0
Evolving Voices Based on Temporal Poisson Factorisation—0
Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models—0
Expertise Mining for Enterprise Content Management—0
Exploiting Domain Knowledge in Aspect Extraction—0
Exploiting Fine-grained Syntactic Transfer Features to Predict the Compositionality of German Particle Verbs—0
Exploration and Exploitation of Victorian Science in Darwin's Reading Notebooks—0
Exploring Adaptor Grammars for Native Language Identification—0
Exploring Differential Topic Models for Comparative Summarization of Scientific Papers—0
Exploring Temporal Patterns in Emergency Department Triage Notes with Topic Models—0
Exploring Thematic Coherence in Fake News—0
Exploring the Technology Landscape through Topic Modeling, Expert Involvement, and Reinforcement Learning—0
Exploring Topic Discriminating Power of Words in Latent Dirichlet Allocation—0
A Bayesian approach to modeling topic-metadata relationships—0
Exploring Topic-Metadata Relationships with the STM: A Bayesian Approach—0
Extended Topic Model for Word Dependency—0
Extracting Topics with Simultaneous Word Co-occurrence and Semantic Correlation Graphs: Neural Topic Modeling for Short Texts—0
Factorized Topic Models—0
Fast Inference for Interactive Models of Text—0
Fast Learning of Clusters and Topics via Sparse Posteriors—0
Feature discovery and visualization of robot mission data using convolutional autoencoders and Bayesian nonparametric topic models—0
Federated Non-negative Matrix Factorization for Short Texts Topic Modeling with Mutual Information—0
Federated Variational Inference Methods for Structured Latent Variable Models—0
Show:102550
← PrevPage 18 of 36Next →
All datasets20NewsGroupsAG News20 NewsgroupsArxiv HEP-TH citation graphAgNewsNYT

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.69—Unverified
2GSMC_v0.55—Unverified
3vNVDMC_v0.52—Unverified
4ETMC_v0.51—Unverified
5NSTMC_v0.38—Unverified
6ProdLDAC_v0.35—Unverified
#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.49—Unverified
2vNVDMC_v0.44—Unverified
3GSMC_v0.41—Unverified
4ETMC_v0.41—Unverified
5NSTMC_v0.37—Unverified
6ProdLDAC_v0.32—Unverified
#ModelMetricClaimedVerifiedStatus
1NVDMTest perplexity836—Unverified
2Bayesian SMMTest perplexity515—Unverified
#ModelMetricClaimedVerifiedStatus
1JoSHMACC83.24—Unverified
2TopicEqTopic Coherence@500.1—Unverified
#ModelMetricClaimedVerifiedStatus
1vONTSSC_v0.49—Unverified
#ModelMetricClaimedVerifiedStatus
1JoSHMACC90.91—Unverified