S. Michos, E. Stamatatos, N. Fakotakis, G. Kokkinakis
{"title":"基于文体方面的经验文本分类计算模型","authors":"S. Michos, E. Stamatatos, N. Fakotakis, G. Kokkinakis","doi":"10.1109/TAI.1996.560403","DOIUrl":null,"url":null,"abstract":"The presented work is strongly motivated by the need for categorizing unrestricted text in terms of a functional style (FS) in order to attain a satisfying outcome in style processing. Towards this aim, a three level description of FS is given that comprises: (a) the basic categories of FS; (b) the main features that characterize each one of the above categories; and (c) the linguistic identifiers that act as style markers in text for the identification of the above features. Special emphasis is put on the problems that faced the computational implementation of the aforementioned findings, as well as the selection of the most appropriate stylometrics (i.e., stylistic scores) to achieve better results on text categorization. This approach is language independent, empirically driven, and can be used in various applications including grammar and style checking, natural language generation, style verification in real world text, and recognition of style shift between adjacent portions of text.","PeriodicalId":209171,"journal":{"name":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1996-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"An empirical text categorizing computational model based on stylistic aspects\",\"authors\":\"S. Michos, E. Stamatatos, N. Fakotakis, G. Kokkinakis\",\"doi\":\"10.1109/TAI.1996.560403\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The presented work is strongly motivated by the need for categorizing unrestricted text in terms of a functional style (FS) in order to attain a satisfying outcome in style processing. Towards this aim, a three level description of FS is given that comprises: (a) the basic categories of FS; (b) the main features that characterize each one of the above categories; and (c) the linguistic identifiers that act as style markers in text for the identification of the above features. Special emphasis is put on the problems that faced the computational implementation of the aforementioned findings, as well as the selection of the most appropriate stylometrics (i.e., stylistic scores) to achieve better results on text categorization. This approach is language independent, empirically driven, and can be used in various applications including grammar and style checking, natural language generation, style verification in real world text, and recognition of style shift between adjacent portions of text.\",\"PeriodicalId\":209171,\"journal\":{\"name\":\"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence\",\"volume\":\"52 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1996-11-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1996.560403\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1996.560403","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An empirical text categorizing computational model based on stylistic aspects
The presented work is strongly motivated by the need for categorizing unrestricted text in terms of a functional style (FS) in order to attain a satisfying outcome in style processing. Towards this aim, a three level description of FS is given that comprises: (a) the basic categories of FS; (b) the main features that characterize each one of the above categories; and (c) the linguistic identifiers that act as style markers in text for the identification of the above features. Special emphasis is put on the problems that faced the computational implementation of the aforementioned findings, as well as the selection of the most appropriate stylometrics (i.e., stylistic scores) to achieve better results on text categorization. This approach is language independent, empirically driven, and can be used in various applications including grammar and style checking, natural language generation, style verification in real world text, and recognition of style shift between adjacent portions of text.