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 401425 of 881 papers

TitleStatusHype
A NoSQL Data-based Personalized Recommendation System for C2C e-Commerce0
Unveiling the semantic structure of text documents using paragraph-aware Topic Models0
Large-Scale Stochastic Sampling from the Probability SimplexCode0
Nonparametric Topic Modeling with Neural Inference0
Overlapping Clustering Models, and One (class) SVM to Bind Them All0
Aspect Sentiment Model for Micro ReviewsCode0
Learning Multilingual Topics from Incomparable Corpus0
Topic Modelling of Empirical Text Corpora: Validity, Reliability, and Reproducibility in Comparison to Semantic Maps0
Transfer Topic Labeling with Domain-Specific Knowledge Base: An Analysis of UK House of Commons Speeches 1935-20140
Neural Storyline Extraction Model for Storyline Generation from News Articles0
Di-LSTM Contrast : A Deep Neural Network for Metaphor Detection0
Deep Dungeons and Dragons: Learning Character-Action Interactions from Role-Playing Game Transcripts0
Deep Dirichlet Multinomial RegressionCode0
Relevant Emotion Ranking from Text Constrained with Emotion Relationships0
A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topicsCode0
Metaphor Suggestions based on a Semantic Metaphor Repository0
Sarcasm Target Identification: Dataset and An Introductory ApproachCode0
Retrofitting Word Representations for Unsupervised Sense Aware Word Similarities0
Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation0
Predicting Good Configurations for GitHub and Stack Overflow Topic Models0
Learning Topics using Semantic Locality0
Towards Training Probabilistic Topic Models on Neuromorphic Multi-chip Systems0
Microblog Topic Identification using Linked Open Data0
Computer-Assisted Text Analysis for Social Science: Topic Models and Beyond0
Scalable Generalized Dynamic Topic ModelsCode0
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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