Scientists' Research Topic Evolution Analysis Based on LDA Topic Model

Topic words analysis based on LDA model

Social network analysis (SNA), which is a research field describing and modeling the social connection of a certain group of people, is popular among network services. Our topic words analysis project is a SNA method to visualize the topic words among emails from Obama.com to accounts registered in Columbus, Ohio. Based on Latent Dirichlet Allocation (LDA) model, a popular topic model of SNA, o...

A Text Mining Research Based on Lda Topic Modelling

A Large number of digital text information is generated every day. Effectively searching, managing and exploring the text data has become a main task. In this paper, we first represent an introduction to text mining and a probabilistic topic model Latent Dirichlet allocation. Then two experiments are proposed Wikipedia articles and users’ tweets topic modelling. The former one builds up a docum...

Latent Topic Model Based on Gaussian-LDA for Audio Retrieval

In this paper,we introduce a new topic model named Gaussian-LDA, which is more suitable to model continuous data. Topic Model based on latent Dirichlet allocation (LDA) is widely used for the statistical analysis of document collections and other discrete data. The LDA model assumes that the words of each document arise from a mixture of topics, each of which is a multinomial distribution over ...

Topic Models - LDA - Experiments

Web Event Topic Analysis by Topic Feature Clustering and Extended LDA Model

To analyze topics of a large number of web events, we proposed an event topic analysis approach by topic feature clustering and extended LDA (latent dirichlet allocation) model. The extended LDA model is dimension LDA (DLDA) which integrates topic probability of LDA model. We represent an event as a multi-dimensions vector and use DLDA model to select topic feature words in events. We aggregate...