用于模式消歧的本体驱动的机械提取器

ACM SE '10 Pub Date : 2010-04-15 DOI:10.1145/1900008.1900049

Sheng Yin, I. Arpinar

{"title":"用于模式消歧的本体驱动的机械提取器","authors":"Sheng Yin, I. Arpinar","doi":"10.1145/1900008.1900049","DOIUrl":null,"url":null,"abstract":"In this paper, we describe an ontology-driven pattern disambiguation process for Rote Extractors. Our approach can generate lexical patterns for a particular relation from unrestricted text. Then patterns can be used to recognize concepts, which have the same relation in other text. We test our experiments with/without the ontology. The results show that our approach can dramatically improve the performance of existing pattern-based Rote Extractors.","PeriodicalId":333104,"journal":{"name":"ACM SE '10","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An ontology-driven rote extractor for pattern disambiguation\",\"authors\":\"Sheng Yin, I. Arpinar\",\"doi\":\"10.1145/1900008.1900049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we describe an ontology-driven pattern disambiguation process for Rote Extractors. Our approach can generate lexical patterns for a particular relation from unrestricted text. Then patterns can be used to recognize concepts, which have the same relation in other text. We test our experiments with/without the ontology. The results show that our approach can dramatically improve the performance of existing pattern-based Rote Extractors.\",\"PeriodicalId\":333104,\"journal\":{\"name\":\"ACM SE '10\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-04-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM SE '10\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1900008.1900049\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SE '10","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1900008.1900049","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

在本文中，我们描述了一个本体驱动的模式消歧过程。我们的方法可以从不受限制的文本中为特定关系生成词汇模式。然后，模式可以用来识别在其他文本中具有相同关系的概念。我们在有/没有本体的情况下测试我们的实验。结果表明，我们的方法可以显著提高现有的基于模式的机械提取器的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

An ontology-driven rote extractor for pattern disambiguation

In this paper, we describe an ontology-driven pattern disambiguation process for Rote Extractors. Our approach can generate lexical patterns for a particular relation from unrestricted text. Then patterns can be used to recognize concepts, which have the same relation in other text. We test our experiments with/without the ontology. The results show that our approach can dramatically improve the performance of existing pattern-based Rote Extractors.

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

ACM SE '10

自引率

0.00%

发文量