Mining both frequent and rare episodes in multiple data streams
文献类型：会议论文
| 作者 | Hu, Zhongyi (1) ; Liu, Wei (1) ; Wang, Hongan (1) |
| 出版日期 | 2013 |
| 会议名称 | 2013 10th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2013 |
| 会议日期 | July 23, 2013 - July 25, 2013 |
| 会议地点 | Shenyang, China |
| 关键词 | data stream mining episode mining rare episode frequent episode multiple data streams |
| 页码 | 753-761 |
| 中文摘要 | In this paper, we describe a method for mining both frequent episodes and rare episodes in multiple data streams. The main issues include episodes mining and data streams relationship processing. Therefore, a mining algorithm together with two dedicated handling mechanisms is presented. We propose the concept of alternative support for discovering frequent and rare episodes, and define the semantic similarity of event sequences for analyzing the relationships between data streams. The algorithm extracts basic episode information from each data stream and keeps the information in episode sets. Then analyze relationships of episode sets and merge similar episode sets, and mining episode rules from the merged sets by alternative support and confidence. From experiments, we find that our mining algorithm is successful for processing multiple data streams and mining frequent and rare episodes. Our research results may lead to a feasible solution for frequent and rare episodes mining in multiple data streams. © 2013 IEEE. |
| 英文摘要 | In this paper, we describe a method for mining both frequent episodes and rare episodes in multiple data streams. The main issues include episodes mining and data streams relationship processing. Therefore, a mining algorithm together with two dedicated handling mechanisms is presented. We propose the concept of alternative support for discovering frequent and rare episodes, and define the semantic similarity of event sequences for analyzing the relationships between data streams. The algorithm extracts basic episode information from each data stream and keeps the information in episode sets. Then analyze relationships of episode sets and merge similar episode sets, and mining episode rules from the merged sets by alternative support and confidence. From experiments, we find that our mining algorithm is successful for processing multiple data streams and mining frequent and rare episodes. Our research results may lead to a feasible solution for frequent and rare episodes mining in multiple data streams. © 2013 IEEE. |
| 收录类别 | CPCI ; EI |
| 会议录出版地 | IEEE Computer Society |
| 语种 | 英语 |
| ISBN号 | 9781467352536 |
| 源URL | [http://ir.iscas.ac.cn/handle/311060/16530]  |
| 专题 | 软件研究所_软件所图书馆_会议论文 |
| 推荐引用方式 GB/T 7714 | Hu, Zhongyi ,Liu, Wei ,Wang, Hongan . Mining both frequent and rare episodes in multiple data streams[C]. 见:2013 10th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2013. Shenyang, China. July 23, 2013 - July 25, 2013. |
入库方式： OAI收割
来源：软件研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。