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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 351–375 of 881 papers

TitleStatusHype
Aspect Extraction through Semi-Supervised Modeling—0
HTMOT : Hierarchical Topic Modelling Over Time—0
Cooperative Hierarchical Dirichlet Processes: Superposition vs. Maximization—0
How Text Segmentation Algorithms Gain from Topic Models—0
Convolutional Dictionary Learning through Tensor Factorization—0
A Societal Sentiment Analysis: Predicting the Values and Ethics of Individuals by Analysing Social Media Content—0
Identifying and Tracking Sentiments and Topics from Social Media Texts during Natural Disasters—0
Identifying Comparable Corpora Using LDA—0
Analysis and tuning of hierarchical topic models based on Renyi entropy approach—0
Identifying Patterns of Associated-Conditions through Topic Models of Electronic Medical Records—0
A Frame of Mind: Using Statistical Models for Detection of Framing and Agenda Setting Campaigns—0
Improved Bayesian Logistic Supervised Topic Models with Data Augmentation—0
Improved Topic Representations of Medical Documents to Assist COVID-19 Literature Exploration—0
A Comparative Study of Methods for Topic Modeling in Spoken Document Retrieval—0
Improving Neural Topic Models by Contrastive Learning with BERT—0
Conversational Structure Aware and Context Sensitive Topic Model for Online Discussions—0
Historia Magistra Vitae: Dynamic Topic Modeling of Roman Literature using Neural Embeddings—0
Hierarchical Topic Presence Models—0
Convergence Rates of Latent Topic Models Under Relaxed Identifiability Conditions—0
Improving Topic Coherence with Regularized Topic Models—0
Improving Topic Model Clustering of Newspaper Comments for Summarisation—0
Improving Topic Models with Latent Feature Word Representations—0
Ask the GRU: Multi-Task Learning for Deep Text Recommendations—0
Improving Users' Demographic Prediction via the Videos They Talk about—0
Hierarchical Re-estimation of Topic Models for Measuring Topical Diversity—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