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 401–450 of 881 papers

TitleStatusHype
Topic Modelling of Empirical Text Corpora: Validity, Reliability, and Reproducibility in Comparison to Semantic Maps—0
Transfer Topic Labeling with Domain-Specific Knowledge Base: An Analysis of UK House of Commons Speeches 1935-2014—0
Di-LSTM Contrast : A Deep Neural Network for Metaphor Detection—0
Deep Dirichlet Multinomial RegressionCode0
Deep Dungeons and Dragons: Learning Character-Action Interactions from Role-Playing Game Transcripts—0
Relevant Emotion Ranking from Text Constrained with Emotion Relationships—0
Neural Storyline Extraction Model for Storyline Generation from News Articles—0
A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topicsCode0
Sarcasm Target Identification: Dataset and An Introductory ApproachCode0
Metaphor Suggestions based on a Semantic Metaphor Repository—0
Retrofitting Word Representations for Unsupervised Sense Aware Word Similarities—0
Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation—0
Predicting Good Configurations for GitHub and Stack Overflow Topic Models—0
Learning Topics using Semantic Locality—0
Towards Training Probabilistic Topic Models on Neuromorphic Multi-chip Systems—0
Microblog Topic Identification using Linked Open Data—0
Computer-Assisted Text Analysis for Social Science: Topic Models and Beyond—0
Scalable Generalized Dynamic Topic ModelsCode0
Application of Rényi and Tsallis Entropies to Topic Modeling Optimization—0
Classifying Idiomatic and Literal Expressions Using Topic Models and Intensity of EmotionsCode0
The Development of Darwin's Origin of Species—0
Learning Topic Models by Neighborhood Aggregation—0
Discovering Hidden Topical Hubs and Authorities in Online Social Networks—0
Attention based Sentence Extraction from Scientific Articles using Pseudo-Labeled data—0
Large-Scale Validation of Hypothesis Generation Systems via Candidate Ranking—0
An Instability in Variational Inference for Topic Models—0
Netizen-Style Commenting on Fashion Photos: Dataset and Diversity Measures—0
Creative Exploration Using Topic Based Bisociative Networks—0
Topic Modeling on Health Journals with Regularized Variational InferenceCode0
Knowledge-based Word Sense Disambiguation using Topic Models—0
Advice from the Oracle: Really Intelligent Information Retrieval—0
A Bayesian Nonparametric Topic Model with Variational Auto-Encoders—0
Multilingual Topic Models—0
A Novel Document Generation Process for Topic Detection based on Hierarchical Latent Tree Models—0
Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models—0
Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes—0
Prediction-Constrained Topic Models for Antidepressant Recommendation—0
Feature discovery and visualization of robot mission data using convolutional autoencoders and Bayesian nonparametric topic models—0
State Space LSTM Models with Particle MCMC Inference—0
Application of Natural Language Processing to Determine User Satisfaction in Public Services—0
A Double Parametric Bootstrap Test for Topic Models—0
Prior-aware Dual Decomposition: Document-specific Topic Inference for Spectral Topic Models—0
Identifying Patterns of Associated-Conditions through Topic Models of Electronic Medical Records—0
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
Topic Modeling based on Keywords and ContextCode1
SpectralLeader: Online Spectral Learning for Single 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