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 851–881 of 881 papers

TitleStatusHype
Evaluating Joint Modeling of Yeast Biology Literature and Protein-Protein Interaction Networks—0
Shared Components Topic Models—0
How Text Segmentation Algorithms Gain from Topic Models—0
Apples to Oranges: Evaluating Image Annotations from Natural Language Processing Systems—0
Identifying Comparable Corpora Using LDA—0
Posterior contraction of the population polytope in finite admixture models—0
On Smoothing and Inference for Topic ModelsCode0
Concept-based Selectional Preferences and Distributional Representations from Wikipedia Articles—0
Constructing a Class-Based Lexical Dictionary using Interactive Topic Models—0
Expertise Mining for Enterprise Content Management—0
Learning Topic Models - Going beyond SVDCode0
Sweeping through the Topic Space: Bad luck? Roll again!—0
Incorporating Lexical Priors into Topic Models—0
Detecting Highly Confident Word Translations from Comparable Corpora without Any Prior Knowledge—0
Word Sense Induction for Novel Sense Detection—0
A Comparative Study of Methods for Topic Modeling in Spoken Document Retrieval—0
The Doubly Correlated Nonparametric Topic Model—0
Improving Topic Coherence with Regularized Topic Models—0
Large-Scale Sparse Principal Component Analysis with Application to Text Data—0
Online Learning for Latent Dirichlet Allocation—0
Synergies in learning words and their referents—0
Learning concept graphs from text with stick-breaking priors—0
Large Margin Learning of Upstream Scene Understanding Models—0
Supervised Topic ModelsCode0
Software Framework for Topic Modelling with Large CorporaCode0
A Bayesian Analysis of Dynamics in Free Recall—0
Rethinking LDA: Why Priors Matter—0
Asynchronous Distributed Learning of Topic Models—0
DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification—0
Syntactic Topic Models—0
Latent Dirichlet AllocationCode1
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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