利用LDA的领域新兴主题探测技术综述

本文以LDA为基础，系统地梳理了新兴主题探测以及主题趋势探测技术中的LDA以及其他LDA改进主题模型(topic model)的发展现状。介绍了LDA的变分推导和Gibbs抽样两种参数推导算法；梳理了近年来对LDA模型的改进，包括对主题演化建模的主题模型、对文档内容和元数据联合建模的模型、采用在线式学习的主题模型及将LDA和引文分析相结合的主题演化方法等，并对不同的改进模型进行了深入对比和分析；梳理了NIH-VB, TIARA,VxInsight等几种主要的主题模型可视化技术。最后通过对LDA模型的总结分析，探讨了利用LDA模型探测领域新兴主题时的关键研究问题。&nbsp;LDA Based，this paper reviews the development of the LDA model and several models which improve the LDA for the filed emerging topic detection.The paper describes two parameter inference algorithms of variational derivation and Gibbs sampling;and reviews the improvement to the LDA in recent years,including the one modeling the evolution of the topics,the one modeling jointly with the content of the document and the meta data,the one with online learning ,the the topic evolution method combines LDA and citation analysis and so on;then compares and analyses the different kinds of improvement models in details; then reviews NIH-VB,TIARA,VxInsight etc of several main visualization techniques. Finally, according to the compare and analysis to the LDA, author discusses the key research problems of detecting the emerging topic by using LDA.<br /