| 基于本体的俄文新闻话题检测设计与实现 |
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| 引用本文： | 原伟,唐亮,易绵竹.基于本体的俄文新闻话题检测设计与实现[J].山东大学学报(理学版),2018,53(9):49-54. |
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| 作者姓名： | 原伟 唐亮 易绵竹 |
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| 作者单位： | 1.上海外国语大学博士后流动站, 上海 200083;2.信息工程大学洛阳校区, 河南 洛阳 471003 |
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| 基金项目： | 国家社会科学基金资助项目(14CYY051,18BYY235);中国博士后科学基金面上资助项目(2017M610268,2018T110403) |
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| 摘 要： | 针对俄文新闻文本的话题检测问题,以俄文文本的自动形态分析、命名实体识别作为辅助手段,设计了一种基于本体描述俄文新闻文本和话题信息并进行相似度计算的方法,随后使用Single-pass算法进行俄文文本的话题检测实验。通过对比基于向量空间模型和基于本体模型的俄文话题检测结果,证明了后者具有相对较高的准确性和有效性。
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| 关 键 词： | 本体 话题检测 俄语 |
| 收稿时间： | 2017-12-22 |
Design and implementation of topic detection in Russian news based on ontology |
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| Institution: | 1. Post-Doctoral Research Station of Shanghai International Studies University, Shanghai 200083, China;2. Information Engineering University, Luoyang 471003, Henan, China |
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| Abstract: | Aiming at the problem of topic detection in Russian news, using automatic morphological analysis and named entity recognition as the auxiliary means, a method for describing Russian news elements and calculating their similarities based on ontology was designed. The Single-pass algorithm was used to carry out text clustering experiments for topic detection. By comparing the results of vector space model(VSM)model and ontology model, it is proved that the latter has relatively high accuracy and validity. |
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| Keywords: | topic detection Russian ontology |
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