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 576–600 of 881 papers

TitleStatusHype
Legal document retrieval across languages: topic hierarchies based on synsets—0
Legal-ES: A Set of Large Scale Resources for Spanish Legal Text Processing—0
Less is More: Learning Prominent and Diverse Topics for Data Summarization—0
Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation—0
Let the Pretrained Language Models "Imagine" for Short Texts Topic Modeling—0
Leveraging Meta Information in Short Text Aggregation—0
Lifelong Neural Topic Learning in Contextualized Autoregressive Topic Models of Language via Informative Transfers—0
Likelihood estimation of sparse topic distributions in topic models and its applications to Wasserstein document distance calculations—0
Limbic: Author-Based Sentiment Aspect Modeling Regularized with Word Embeddings and Discourse Relations—0
Linguistic Resources and Topic Models for the Analysis of Persian Poems—0
Linking Tweets to News: A Framework to Enrich Short Text Data in Social Media—0
Local and Global Topics in Text Modeling of Web Pages Nested in Web Sites—0
"Look Ma, No Hands!" A Parameter-Free Topic Model—0
LTSG: Latent Topical Skip-Gram for Mutually Learning Topic Model and Vector Representations—0
Making sense of violence risk predictions using clinical notes—0
Managing sparsity, time, and quality of inference in topic models—0
Matrix and Tensor Factorization Methods for Natural Language Processing—0
Measuring daily-life fear perception change: a computational study in the context of COVID-19—0
Measuring the Similarity between Automatically Generated Topics—0
Measuring Topic Coherence through Optimal Word Buckets—0
Metaphor Suggestions based on a Semantic Metaphor Repository—0
Microblog Topic Identification using Linked Open Data—0
Mining Argumentative Structure from Natural Language text using Automatically Generated Premise-Conclusion Topic Models—0
Mixed Membership Markov Models for Unsupervised Conversation Modeling—0
Mixed Membership Word Embeddings for Computational Social Science—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