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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.

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Latest papers without code

Deep Probabilistic Graphical Modeling

25 Apr 2021

We develop reweighted expectation maximization, an algorithm that unifies several existing maximum likelihood-based algorithms for learning models parameterized by neural networks.

TOPIC MODELS

Few-shot Learning for Topic Modeling

19 Apr 2021

The proposed method trains the neural networks such that the expected test likelihood is improved when topic model parameters are estimated by maximizing the posterior probability using the priors based on the EM algorithm.

FEW-SHOT LEARNING TOPIC MODELS

Hierarchical Topic Presence Models

16 Apr 2021

Motivated by a data set of web pages (documents) nested in web sites, we extend the Poisson factor analysis topic model to hierarchical topic presence models for analyzing text from documents nested in known groups.

DATA AUGMENTATION TOPIC MODELS

AI supported Topic Modeling using KNIME-Workflows

15 Apr 2021

The focus of this work is on the implementation of the knowledge-based topic modelling services in a KNIME workflow.

TEXT SUMMARIZATION TOPIC MODELS

Local and Global Topics in Text Modeling of Web Pages Nested in Web Sites

30 Mar 2021

For web pages nested inside web sites, local topic models explicitly label local topics and identifies the owning web site.

HIERARCHICAL STRUCTURE TOPIC MODELS

Term-community-based topic detection with variable resolution

25 Mar 2021

Network-based procedures for topic detection in huge text collections offer an intuitive alternative to probabilistic topic models.

COMMUNITY DETECTION TOPIC MODELS

Bridging the gap between supervised classification and unsupervised topic modelling for social-media assisted crisis management

22 Mar 2021

Social media such as Twitter provide valuable information to crisis managers and affected people during natural disasters.

DOMAIN ADAPTATION TOPIC MODELS

Topic Modelling Meets Deep Neural Networks: A Survey

28 Feb 2021

Topic modelling has been a successful technique for text analysis for almost twenty years.

TEXT GENERATION TOPIC MODELS

Analysis and tuning of hierarchical topic models based on Renyi entropy approach

19 Jan 2021

In this paper, we propose a Renyi entropy-based approach for a partial solution to the above problem.

TOPIC MODELS

User Ex Machina : Simulation as a Design Probe in Human-in-the-Loop Text Analytics

6 Jan 2021

Topic models are widely used analysis techniques for clustering documents and surfacing thematic elements of text corpora.

TOPIC MODELS