{"title":"一种基于语义特征的逻辑分段方法及其应用","authors":"Zhenfang Zhu, Peiyu Liu, Ran Lu, Xuezhi Chi","doi":"10.1109/ITIME.2009.5236216","DOIUrl":null,"url":null,"abstract":"In this paper, we introduced a new matching method based on logic-centered paragraphs. This method is built on the concept dictionary, in this method, the paragraphs which have the same meaning will be clustered by analyzing the logical concept of the text to be classified, and establish the logical paragraphs on the basis of the division method of logical levels. Then put the text to be classified in the right classification, which considered the contribution to the theme of different paragraphs in the text. At the same time, in order to solve problem of synonyms and polysemy in the texts to be classified, we introduced the expansion of the synonyms concept and related words. Experimental results show that this method can improve the effectiveness of classification, and a higher accuracy rate can be obtained in content flitting.","PeriodicalId":398477,"journal":{"name":"2009 IEEE International Symposium on IT in Medicine & Education","volume":"110 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A logical paragraph division based on semantic characteristics and its application\",\"authors\":\"Zhenfang Zhu, Peiyu Liu, Ran Lu, Xuezhi Chi\",\"doi\":\"10.1109/ITIME.2009.5236216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we introduced a new matching method based on logic-centered paragraphs. This method is built on the concept dictionary, in this method, the paragraphs which have the same meaning will be clustered by analyzing the logical concept of the text to be classified, and establish the logical paragraphs on the basis of the division method of logical levels. Then put the text to be classified in the right classification, which considered the contribution to the theme of different paragraphs in the text. At the same time, in order to solve problem of synonyms and polysemy in the texts to be classified, we introduced the expansion of the synonyms concept and related words. Experimental results show that this method can improve the effectiveness of classification, and a higher accuracy rate can be obtained in content flitting.\",\"PeriodicalId\":398477,\"journal\":{\"name\":\"2009 IEEE International Symposium on IT in Medicine & Education\",\"volume\":\"110 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Symposium on IT in Medicine & Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITIME.2009.5236216\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Symposium on IT in Medicine & Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITIME.2009.5236216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A logical paragraph division based on semantic characteristics and its application
In this paper, we introduced a new matching method based on logic-centered paragraphs. This method is built on the concept dictionary, in this method, the paragraphs which have the same meaning will be clustered by analyzing the logical concept of the text to be classified, and establish the logical paragraphs on the basis of the division method of logical levels. Then put the text to be classified in the right classification, which considered the contribution to the theme of different paragraphs in the text. At the same time, in order to solve problem of synonyms and polysemy in the texts to be classified, we introduced the expansion of the synonyms concept and related words. Experimental results show that this method can improve the effectiveness of classification, and a higher accuracy rate can be obtained in content flitting.