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

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Showing 276–300 of 881 papers

TitleStatusHype
Keyword Assisted Topic ModelsCode1
Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic CoherenceCode2
A Graph Convolutional Topic Model for Short and Noisy Text StreamsCode1
Know thy corpus! Robust methods for digital curation of Web corporaCode0
Generalized Gumbel-Softmax Gradient Estimator for Generic Discrete Random Variables—0
Gaussian Hierarchical Latent Dirichlet Allocation: Bringing Polysemy Back—0
Conversational Structure Aware and Context Sensitive Topic Model for Online Discussions—0
Constrained Relational Topic ModelsCode0
Optimal estimation of sparse topic models—0
Random-walk Based Generative Model for Classifying Document Networks—0
VSEC-LDA: Boosting Topic Modeling with Embedded Vocabulary Selection—0
CATVI: Conditional and Adaptively Truncated Variational Inference for Hierarchical Bayesian Nonparametric ModelsCode0
Topic Extraction of Crawled Documents Collection using Correlated Topic Model in MapReduce Framework—0
Topic Models with Survival Supervision: Archetypal Analysis and Neural Approaches—0
Precision-Recall Balanced Topic Modelling—0
Legal document retrieval across languages: topic hierarchies based on synsets—0
Tracing State-Level Obesity Prevalence from Sentence Embeddings of Tweets: A Feasibility Study—0
Discovering topics with neural topic models built from PLSA assumptions—0
FLATM: A Fuzzy Logic Approach Topic Model for Medical Documents—0
Topical Phrase Extraction from Clinical Reports by Incorporating both Local and Global Context—0
A Coefficient of Determination for Probabilistic Topic ModelsCode0
Prediction Focused Topic Models for Electronic Health Records—0
A Multilingual Topic Model for Learning Weighted Topic Links Across Corpora with Low Comparability—0
Statistical Model Aggregation via Parameter MatchingCode0
Neural Topic Model with Reinforcement Learning—0
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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