基于多序列比对的多词表达式识别

Ru Li, Lijun Zhong, Jianyong Duan
{"title":"基于多序列比对的多词表达式识别","authors":"Ru Li, Lijun Zhong, Jianyong Duan","doi":"10.1109/ALPIT.2008.71","DOIUrl":null,"url":null,"abstract":"For the Multiword Expression (MWE) recognition, the Multiple Sequence Alignment (MSA) is proposed on the motivation of gene recognition. Because textual sequence is similar to gene sequence in pattern analysis. This MSA technique is combined with error-driven rules, with the improved efficiency beyond the traditional methods.It provides a guarantee for the MWE recall. It uses the dynamic programming method to prevent candidates from combinational explosion, and provides a global solution for pattern extraction instead of sub-pattern redundancy. Consequently, it has accurate measures for flexible patterns. In experiment, some advanced statistical measures are performed for ranking candidates. In the comparison experiment, the MSA approach achieved better results.","PeriodicalId":169222,"journal":{"name":"2008 International Conference on Advanced Language Processing and Web Information Technology","volume":"377 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Multiword Expression Recognition Using Multiple Sequence Alignment\",\"authors\":\"Ru Li, Lijun Zhong, Jianyong Duan\",\"doi\":\"10.1109/ALPIT.2008.71\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the Multiword Expression (MWE) recognition, the Multiple Sequence Alignment (MSA) is proposed on the motivation of gene recognition. Because textual sequence is similar to gene sequence in pattern analysis. This MSA technique is combined with error-driven rules, with the improved efficiency beyond the traditional methods.It provides a guarantee for the MWE recall. It uses the dynamic programming method to prevent candidates from combinational explosion, and provides a global solution for pattern extraction instead of sub-pattern redundancy. Consequently, it has accurate measures for flexible patterns. In experiment, some advanced statistical measures are performed for ranking candidates. In the comparison experiment, the MSA approach achieved better results.\",\"PeriodicalId\":169222,\"journal\":{\"name\":\"2008 International Conference on Advanced Language Processing and Web Information Technology\",\"volume\":\"377 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Conference on Advanced Language Processing and Web Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ALPIT.2008.71\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Advanced Language Processing and Web Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ALPIT.2008.71","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

针对多词表达(MWE)识别,提出了基于基因识别动机的多序列比对(MSA)方法。因为文本序列在模式分析中与基因序列相似。该技术与错误驱动规则相结合,提高了传统方法的效率。它为MWE的召回提供了保证。它采用动态规划的方法来防止候选模式的组合爆炸,并为模式提取提供了一种全局解决方案,而不是子模式冗余。因此,它具有灵活模式的精确度量。在实验中,采用了一些先进的统计方法对候选人进行排名。在对比实验中,MSA方法取得了更好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiword Expression Recognition Using Multiple Sequence Alignment
For the Multiword Expression (MWE) recognition, the Multiple Sequence Alignment (MSA) is proposed on the motivation of gene recognition. Because textual sequence is similar to gene sequence in pattern analysis. This MSA technique is combined with error-driven rules, with the improved efficiency beyond the traditional methods.It provides a guarantee for the MWE recall. It uses the dynamic programming method to prevent candidates from combinational explosion, and provides a global solution for pattern extraction instead of sub-pattern redundancy. Consequently, it has accurate measures for flexible patterns. In experiment, some advanced statistical measures are performed for ranking candidates. In the comparison experiment, the MSA approach achieved better results.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信