Micro-blog topic detection algorithm based on topic model

Hua-jun HUANG; Jun-shan TAN; Jiao-hua QIN

doi:10.11959/j.issn.2096-109x.2016.00049

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Micro-blog topic detection algorithm based on topic model

Papers | 更新时间：2024-06-03

- Micro-blog topic detection algorithm based on topic model
- Chinese Journal of Network and Information Security Vol. 2, Issue 5, Pages: 30-38(2016)
- 作者机构：
- 作者简介：
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- DOI：10.11959/j.issn.2096-109x.2016.00049
  CLC： TP391
- Online First：2016-05，
  
  Published：15 May 2016
- 稿件说明：
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Hua-jun HUANG, Jun-shan TAN, Jiao-hua QIN. Micro-blog topic detection algorithm based on topic model[J]. Chinese Journal of Network and Information Security, 2016, 2(5): 30-38.
DOI：

Hua-jun HUANG, Jun-shan TAN, Jiao-hua QIN. Micro-blog topic detection algorithm based on topic model[J]. Chinese Journal of Network and Information Security, 2016, 2(5): 30-38. DOI： 10.11959/j.issn.2096-109x.2016.00049.

摘要

摘要：微博数据的实时、大规模、短文本以及富含噪声等特征为话题检测带来新的挑战，传统向量空模型（VSM）表示文本无法很好地对其进行建模。基于此，提出一种基于主题模型的微博话题检测算法。首先，对微博数据构建文档词条矩阵和词语夫联矩阵来提取主题词；然后，对主题词进行聚类，得到主题模型；最后，利用文本与主题模型相互匹配实现文本聚类，从而达到话题检测的目的。实验结果表示，该算法能有效地进行话题聚类并检测出话题，在最佳参数组合条件下，其各类别的平均F值达到95%以上。

Abstract

Micro-blog data has the characteristic of real-time

volume

short-text

and noise-rich.So it is a challenge for the traditional topic detection technology.A novel micro-blog topic detection algorithm based on topic model was proposed.Firstly

the micro-blog data was expressed as text word matrix and word relation matrix.The topic word was extracted from the two vectors.Secondly

the topic model was obtained with clustering.Finally

the topic detection of micro-blog was obtained by clustering text and topic model.Experimental results show that the algorithm proposed can effectively detection the text topic

and with the best parameter group of precision

recall rate

and the value F is about 95%.

关键词

Keywords

references

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