| 基于增量主题模型的微博在线事件分析 |
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| 引用本文： | 马慧芳,王博.基于增量主题模型的微博在线事件分析[J].计算机工程,2013,39(3):191-196. |
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| 作者姓名： | 马慧芳 王博 |
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| 作者单位： | 1. 西北师范大学计算机科学与工程学院,兰州,730070
2. 解放军南京政治学院上海校区军事信息管理系,上海,200433 |
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| 基金项目： | 国家自然科学基金资助项目(61163039)；西北师范大学青年教师科研能力提升计划骨干基金资助项目(NWNU- LKQN-10-1) |
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| 摘 要： | 为更好地利用微博结构化社会网络方面的信息，提出一种基于增量主题模型的微博在陑事件分析算法。通过设计增量过程，保留已有的训练信息，采用自适应非对称学习算法融入新微博内容与用户关系。实验结果表明，该算法可在短暂的时间内建模，并有效提高事件分析的性能。
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| 关 键 词： | 用户关系 话题检测与追踪 主题模型 自适应 增量概率 增量算法 |
| 收稿时间： | 2012-04-09 |
Microblog Online Event Analysis Based on Incremental Topic Model |
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| MA Hui-fang
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WANG Bo.Microblog Online Event Analysis Based on Incremental Topic Model[J].Computer Engineering,2013,39(3):191-196. |
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| Authors: | MA Hui-fang WANG Bo |
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| Affiliation: | (1. College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China; 2. Department of Military Information Management, Shanghai Branch of PLA Nanjing Institute of Politics, Shanghai 200433, China) |
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| Abstract: | Aiming at the existing event analysis algorithms do not make full use of the structure information on social network of microblogs, this paper proposes a microblog online event analysis algorithm based on incremental topic model. This algorithm designs a reasonable incremental process to preserve the existing training information, and gives an adaptive asymmetric learning mechanism to integrate the content and user relationship of new microblogs. Experimental results show that this algorithm leads to more balanced and comprehensive improvement for online event detection in near real-time scenarios. |
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| Keywords: | user relationship Topic Detection and Tracking(TDT) topic model adaptive incremental probability incremental algorithm |
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