{"title":"用于Web 2.0的事件提取方法","authors":"A. Elkhlifi, R. Faiz","doi":"10.1109/AICCSA.2010.5587014","DOIUrl":null,"url":null,"abstract":"Event extraction is a significant task in information extraction. This importance increases more and more with the explosion of textual data available on the Web, the appearance of Web 2.0 and the tendency towards the Semantic Web. Thus, we propose a generic approach to extract events from text and to analyze them. We propose an event extraction algorithm with a polynomial complexity O(n5), and a new similarity measurement between events. We use this measurement to gather similar events. We also present a semantic map of events, and we validate the first component of our approach by the development of the “EventEC” system.","PeriodicalId":352946,"journal":{"name":"ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Event extraction approach for Web 2.0\",\"authors\":\"A. Elkhlifi, R. Faiz\",\"doi\":\"10.1109/AICCSA.2010.5587014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Event extraction is a significant task in information extraction. This importance increases more and more with the explosion of textual data available on the Web, the appearance of Web 2.0 and the tendency towards the Semantic Web. Thus, we propose a generic approach to extract events from text and to analyze them. We propose an event extraction algorithm with a polynomial complexity O(n5), and a new similarity measurement between events. We use this measurement to gather similar events. We also present a semantic map of events, and we validate the first component of our approach by the development of the “EventEC” system.\",\"PeriodicalId\":352946,\"journal\":{\"name\":\"ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AICCSA.2010.5587014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS/IEEE International Conference on Computer Systems and Applications - AICCSA 2010","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICCSA.2010.5587014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Event extraction is a significant task in information extraction. This importance increases more and more with the explosion of textual data available on the Web, the appearance of Web 2.0 and the tendency towards the Semantic Web. Thus, we propose a generic approach to extract events from text and to analyze them. We propose an event extraction algorithm with a polynomial complexity O(n5), and a new similarity measurement between events. We use this measurement to gather similar events. We also present a semantic map of events, and we validate the first component of our approach by the development of the “EventEC” system.