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 776–800 of 881 papers

TitleStatusHype
Continuous Time Dynamic Topic Models—0
Contrastive News and Social Media Linking using BERT for Articles and Tweets across Dual Platforms—0
Convergence Rates of Latent Topic Models Under Relaxed Identifiability Conditions—0
Conversational Structure Aware and Context Sensitive Topic Model for Online Discussions—0
Convolutional Dictionary Learning through Tensor Factorization—0
Cooperative Hierarchical Dirichlet Processes: Superposition vs. Maximization—0
Creating POS Tagging and Dependency Parsing Experts via Topic Modeling—0
Creative Exploration Using Topic Based Bisociative Networks—0
Credible Review Detection with Limited Information using Consistency Analysis—0
Cross-lingual Pseudo Relevance Feedback Based on Weak Relevant Topic Alignment—0
Cross-Lingual Topic Alignment in Time Series Japanese / Chinese News—0
Data-Driven Broad-Coverage Grammars for Opinionated Natural Language Generation (ONLG)—0
Decentralized Topic Modelling with Latent Dirichlet Allocation—0
Deep Dungeons and Dragons: Learning Character-Action Interactions from Role-Playing Game Transcripts—0
Deep Poisson Factor Modeling—0
Deep Probabilistic Graphical Modeling—0
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network—0
Deep Temporal-Recurrent-Replicated-Softmax for Topical Trends over Time—0
Deep topic modeling by multilayer bootstrap network and lasso—0
Deep Topic Models for Multi-label Learning—0
Dense v.s. Sparse: A Comparative Study of Sampling Analysis in Scene Classification of High-Resolution Remote Sensing Imagery—0
Detecting Highly Confident Word Translations from Comparable Corpora without Any Prior Knowledge—0
Detecting Neurocognitive Disorders through Analyses of Topic Evolution and Cross-modal Consistency in Visual-Stimulated Narratives—0
Detecting Sarcasm Using Different Forms Of Incongruity—0
Developing a Curated Topic Model for COVID-19 Medical Research Literature—0
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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