| 基于改进向量空间模型的话题识别与跟踪 |
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| 引用本文： | 宋丹,王卫东,陈英.基于改进向量空间模型的话题识别与跟踪[J].微机发展,2006,16(9):62-64. |
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| 作者姓名： | 宋丹 王卫东 陈英 |
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| 作者单位： | 大连理工大学计算机科学与工程系 辽宁大连116024(宋丹)，东北电力大学计算机系 吉林吉林132012(王卫东，陈英) |
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| 摘 要： | 话题识别与跟踪旨在发展一系列基于事件的信息组织技术,通过监测以实现对新闻媒体信息流中新话题的自动识别和已知话题的动态跟踪。文中提供一种利用改进的向量空间模型进行识别和跟踪的方法。没有使用传统向量空间模型中单个向量,而是按照语义将特征词划分为4个组(人物、时间、地点、内容)并形成4个向量空间。每个空间进行独立的权重计算和相似度计算。实验证明这些方法是有效的。
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| 关 键 词： | 话题识别与跟踪 向量空间模型 时间表达 |
| 文章编号： | 1673-629X(2006)09-0062-03 |
| 修稿时间： | 2005年12月1日 |
Topic Detection and Tracking with a Developed Vector Space Model |
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| SONG Dan,WANG Wei-dong,CHEN Ying.Topic Detection and Tracking with a Developed Vector Space Model[J].Microcomputer Development,2006,16(9):62-64. |
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| Authors: | SONG Dan WANG Wei-dong CHEN Ying |
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| Affiliation: | SONG Dan~1,WANG Wei-dong~2,CHEN Ying~2 |
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| Abstract: | Topic detection and tracking is an event-based information organization task where online new streams are monitored in order to spot new unreported events and link documents with previously detected events.So present an approach that formalizes temporal expressions and augments spatial terms with ontological information and uses this data in the dictation.In addition,instead using a single term vector as document representation,split the terms into four semantic classes and process,including character,time,space and content,and weigh the classes separately.The approach is motivated by experiment. |
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| Keywords: | topic detection and tracking vector space model temporal expressions |
| 本文献已被 CNKI 等数据库收录！ |
