图 书 馆
用原型选择嵌入向量空间中的图Graph Embedding in Vector Spaces by Means of Prototype Selection |
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| 课程网址: | http://videolectures.net/gbr07_riesen_gevs/ |
| 主讲教师: | Kaspar Riesen |
| 开课单位: | 伯尔尼大学 |
| 开课时间: | 2007-07-12 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The field of statistical pattern recognition is characterized by the use of feature vectors for pattern representation, while strings or, more generally, graphs are prevailing in structural pattern recognition. In this paper we aim at bridging the gap between the domain of feature based and graph based object representation. We propose a general approach for transforming graphs into n-dimensional real vector spaces by means of prototype selection and graph edit distance computation. This method establishes the access to the wide range of procedures based on feature vectors without loosing the representational power of graphs. Through various experimental results we show that the proposed method, using graph embedding and classification in a vector space, outperforms the tradional approach based on k-nearest neighbor classification in the graph domain. |
| 关 键 词: | 统计模式; 字符串; 结构模式 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-15：cwx |
| 阅读次数: | 74 |