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
Labeling Topics with Images using Neural Networks—0
Accounting ngrams and multi-word terms can improve topic models—0
Transductive Adaptation of Black Box Predictions—0
Translating Bayesian Networks into Entity Relationship Models, Extended Version—0
Summarizing Decisions in Spoken Meetings—0
Unsupervised Topic Modeling Approaches to Decision Summarization in Spoken Meetings—0
Source-LDA: Enhancing probabilistic topic models using prior knowledge sourcesCode0
Token-Level Metaphor Detection using Neural Networks—0
NaCTeM at SemEval-2016 Task 1: Inferring sentence-level semantic similarity from an ensemble of complementary lexical and sentence-level features—0
Clustering for Simultaneous Extraction of Aspects and Features from Reviews—0
The UMD CLPsych 2016 Shared Task System: Text Representation for Predicting Triage of Forum Posts about Mental Health—0
Bootstrapping Translation Detection and Sentence Extraction from Comparable Corpora—0
On a Topic Model for SentencesCode0
Online Multilingual Topic Models with Multi-Level Hyperpriors—0
ITNLP-AiKF at SemEval-2016 Task 3 a quesiton answering system using community QA repository—0
Temporal Topic Modeling to Assess Associations between News Trends and Infectious Disease Outbreaks—0
Spectral Methods for Correlated Topic Models—0
Provable Algorithms for Inference in Topic Models—0
Toward a general, scaleable framework for Bayesian teaching with applications to topic models—0
Computing Web-scale Topic Models using an Asynchronous Parameter ServerCode0
Latent Tree Models for Hierarchical Topic DetectionCode0
Inter-Battery Topic Representation Learning—0
Mixing Dirichlet Topic Models and Word Embeddings to Make lda2vecCode0
That'll Do Fine!: A Coarse Lexical Resource for English-Hindi MT, Using Polylingual Topic Models—0
Entities as topic labels: Improving topic interpretability and evaluability combining Entity Linking and Labeled LDA—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