An overview of topic modeling and its current applications in ...

Selecting the Number and Labels of Topics in Topic Modeling

Topic modeling is a type of text analysis that identifies clusters of co-occurring words, or latent topics. A challenging step of topic ...

Topic modelling and text classification models for applications within ...

This report presents an overview of topic modelling and classification models in relation to four case studies in the EFSA project ...

Create a topic model | Conversational Insights Documentation

Note: Topic model creation is a lengthy process and depends on the number of conversations in your training dataset. A job containing the minimum number of ...

Topic Modelling: Overview and Business Applications - YouTube

In this video, I discuss questions like what is topic modelling and what are the applications of topic modelling in business.

Topic models do not model topics: epistemological remarks ... - HAL

An overview of topic modeling and its current applications in bioinformatics. SpringerPlus, 5(1):1608. Liu, X. and Jin, M. (2020) ...

Probabilistic Topic Modeling in Multilingual Settings - Lirias

2.2 A Very Short Overview of Current State-of-the-Art Models. We believe that bilingual LDA (see Appendix A), being the straightforward extension of the LDA.

Topic Modeling and Text Analysis for Qualitative Policy Research ...

In recent years, the computational method of topic modelling (TM) has gained ... “Exploiting Affinities between Topic. Modeling and the Sociological Perspective ...

Introduction to Probabilistic Topic Models - CS@Columbia

In this article, we review the main ideas of this field, survey the current state-of-the-art, and describe some promising future directions. We first ...

Navigating the Local Modes of Big Data: The Case of Topic Models

... LDA and related models but does not mention the ... In Section 6 we will outline very recent research which yields deterministic initializations with excellent ...

Topic Modeling as a Tool for Analyzing Library Chat Transcripts

Lin Liu et al., “An Overview of Topic Modeling and Its Current Applications in Bioinformatics,” Springerplus 5, no. 1608 (September 2016): 1 ...

Topic Modeling for the People - Maria Antoniak

There are many, many different kinds of topic models. However, topic model evaluation is really difficult (see below), and it's particularly ...

A Systematic Review of Topic Modeling Algorithms

This review paper is in four sections. The first and the second section presents an overview of document thematic structure alongside discussion on the ...

LSA, LDA, and Top2Vec - ScholarSpace

While conducting their topic modeling application in their respective disciplines, ... An overview of topic modeling and its current. Page 938. Page 10 ...

Smart literature review: a practical topic modelling approach to ...

It has been predominantly been used in the social sciences to identify concepts and subjects within a corpus of documents. An overview of ...

Topic Modeling - Alteryx Help Documentation

Use Topic Modeling to identify and categorize topics in a body of text. Consider using the Text Pre-processing tool upstream before passing data into the Topic ...

Topic Modeling in Embedding Spaces - MIT Press Direct

Topic modeling analyzes documents to learn meaningful patterns of words. However, existing topic models fail to learn interpretable topics ...

Evaluation Methods for Topic Models

In addition to com- paring evaluation methods that are currently used in the topic modeling literature, we propose several al- ternative methods. We present ...

Interactive Topic Modeling - ACL Anthology

For text, one of the few real-world applications of topic models is corpus ... Instead, we change the underlying model, using the current topic assign-.

On-line LDA: Adaptive Topic Models for Mining Text Streams with ...

Our approach allows the topic modeling framework, specifically the Latent Dirichlet Allocation (LDA) model, to work in an online fashion such that it ...

The Author-Topic Model for Authors and Documents

A number of recent approaches to modeling document content are based upon the idea that the probabil- ity distribution over words in a document can be ex-.