| 一种基于遗传算法的主题划分方法 |
| |
| 引用本文： | 傅间莲,陈群秀. 一种基于遗传算法的主题划分方法[J]. 计算机工程, 2006, 32(11): 209-210,218 |
| |
| 作者姓名： | 傅间莲 陈群秀 |
| |
| 作者单位： | 清华大学计算机系智能技术与系统国家重点实验室,北京,100084 |
| |
| 摘 要： | 提出了一个通过建立段落向量空间模型，根据遗传算法进行文本主题划分的算法，解决了文章的篇章结构分析问题，使得多主题文章的文摘更具内容全面性与结构平衡性。实验结果表明，该算法对多主题文章的主题划分准确率为89.3％，对单主题文章的主题划分准确率为94.6％。
|
| 关 键 词： | 自动文摘 向量空间模型 遗传算法 主题划分 |
| 文章编号： | 1000-3428（2006）11-0209-02 |
| 收稿时间： | 2005-06-26 |
| 修稿时间： | 2005-06-26 |
Study on Topic Partition Based on Genetic Algorithm |
| |
| FU Jianlian,CHEN Qunxiu. Study on Topic Partition Based on Genetic Algorithm[J]. Computer Engineering, 2006, 32(11): 209-210,218 |
| |
| Authors: | FU Jianlian CHEN Qunxiu |
| |
| Affiliation: | State Key Lab of Intelligent Technology and System, Department of Computer Science and Technology, Tsinghua University, Beijing 100084 |
| |
| Abstract: | This paper establishes VSM for the whole article based on paragraph, then prnpnses an idea for multi-topic text partitioning based on GA. It solves the prnblem of chapter structural analysis in multi-topic article and makes the abstract of the multi-topic to have more general content and more balanced structure. The experiment on close test shows that the precision of topic partition for multi-topic text and single-topic text reaches 89.3% and 94.6% respectively. |
| |
| Keywords: | Automatic abstraction Vector space model Genetic algorithm(GA) Topic segmentation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
