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Topic Models

64 papers with code ยท Miscellaneous

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Sparse Parallel Training of Hierarchical Dirichlet Process Topic Models

6 Jun 2019

Nonparametric extensions of topic models such as Latent Dirichlet Allocation, including Hierarchical Dirichlet Process (HDP), are often studied in natural language processing.

TOPIC MODELS

Integration of Knowledge Graph Embedding Into Topic Modeling with Hierarchical Dirichlet Process

NAACL 2019

Leveraging domain knowledge is an effective strategy for enhancing the quality of inferred low-dimensional representations of documents by topic models.

DOCUMENT CLASSIFICATION KNOWLEDGE GRAPH EMBEDDING TOPIC MODELS

Analyzing Bayesian Crosslingual Transfer in Topic Models

NAACL 2019

We introduce a theoretical analysis of crosslingual transfer in probabilistic topic models.

TOPIC MODELS

Microblog Hashtag Generation via Encoding Conversation Contexts

NAACL 2019

Automatic hashtag annotation plays an important role in content understanding for microblog posts.

TOPIC MODELS

A framework for streamlined statistical prediction using topic models

WS 2019

In the Humanities and Social Sciences, there is increasing interest in approaches to information extraction, prediction, intelligent linkage, and dimension reduction applicable to large text corpora.

DIMENSIONALITY REDUCTION TOPIC MODELS

Sign Clustering and Topic Extraction in Proto-Elamite

WS 2019

We describe a first attempt at using techniques from computational linguistics to analyze the undeciphered proto-Elamite script.

TOPIC MODELS

Why Didn't You Listen to Me? Comparing User Control of Human-in-the-Loop Topic Models

23 May 2019

To address the lack of comparative evaluation of Human-in-the-Loop Topic Modeling (HLTM) systems, we implement and evaluate three contrasting HLTM modeling approaches using simulation experiments.

TOPIC MODELS

Microblog Hashtag Generation via Encoding Conversation Contexts

NAACL 2019

Automatic hashtag annotation plays an important role in content understanding for microblog posts.

TOPIC MODELS

Automatic Evaluation of Local Topic Quality

18 May 2019

Topic models are typically evaluated with respect to the global topic distributions that they generate, using metrics such as coherence, but without regard to local (token-level) topic assignments.

TOPIC MODELS

Dirichlet Variational Autoencoder

ICLR 2019

The experimental results show that 1) DirVAE models the latent representation result with the best log-likelihood compared to the baselines; and 2) DirVAE produces more interpretable latent values with no collapsing issues which the baseline models suffer from.

TOPIC MODELS