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 451–475 of 881 papers

TitleStatusHype
Deep Temporal-Recurrent-Replicated-Softmax for Topical Trends over Time—0
Interpretable probabilistic embeddings: bridging the gap between topic models and neural networks—0
Taking into account Inter-sentence Similarity for Update Summarization—0
Information Bottleneck Inspired Method For Chat Text Segmentation—0
Convergence Rates of Latent Topic Models Under Relaxed Identifiability Conditions—0
SpectralLeader: Online Spectral Learning for Single Topic Models—0
MetaLDA: a Topic Model that Efficiently Incorporates Meta informationCode0
Asymptotic Bayesian Generalization Error in Latent Dirichlet Allocation and Stochastic Matrix Factorization—0
Learning to Rank Semantic Coherence for Topic Segmentation—0
Detecting Perspectives in Political DebatesCode0
Detecting Sarcasm Using Different Forms Of Incongruity—0
Adapting Topic Models using Lexical Associations with Tree Priors—0
Why ADAGRAD Fails for Online Topic Modeling—0
Classifying Frames at the Sentence Level in News Articles—0
Latent Space Embedding for Retrieval in Question-Answer Archives—0
A Unified Framework for Structured Prediction: From Theory to Practice—0
Identifying and Tracking Sentiments and Topics from Social Media Texts during Natural Disasters—0
Topic Model Stability for Hierarchical Summarization—0
Mining Argumentative Structure from Natural Language text using Automatically Generated Premise-Conclusion Topic Models—0
Unsupervised Terminological Ontology Learning based on Hierarchical Topic ModelingCode0
Communication-Free Parallel Supervised Topic Models—0
Identifying Reference Spans: Topic Modeling and Word Embeddings help IR—0
Familia: An Open-Source Toolkit for Industrial Topic ModelingCode0
Combining Thesaurus Knowledge and Probabilistic Topic Models—0
Prediction-Constrained Training for Semi-Supervised Mixture and Topic Models—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