D. Vishnyakova, Raul Rodriguez-Esteban, K. Ozol, Fabio Rinaldi
{"title":"基于期刊描述符和语义类型的MEDLINE作者姓名消歧","authors":"D. Vishnyakova, Raul Rodriguez-Esteban, K. Ozol, Fabio Rinaldi","doi":"10.5167/UZH-132256","DOIUrl":null,"url":null,"abstract":"Author name disambiguation (AND) in publication and citation resources is a well-known problem. Often, information about email address and other details in the affiliation is missing. In cases where such information is not available, identifying the authorship of publications becomes very challenging. Consequently, there have been attempts to resolve such cases by utilizing external resources as references. However, such external resources are heterogeneous and are not always reliable regarding the correctness of information. To solve the AND task, especially when information about an author is not complete we suggest the use of new features such as journal descriptors (JD) and semantic types (ST). The evaluation of different feature models shows that their inclusion has an impact equivalent to that of other important features such as email address. Using such features we show that our system outperforms the state of the art.","PeriodicalId":297051,"journal":{"name":"BioTxtM@COLING 2016","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Author Name Disambiguation in MEDLINE Based on Journal Descriptors and Semantic Types\",\"authors\":\"D. Vishnyakova, Raul Rodriguez-Esteban, K. Ozol, Fabio Rinaldi\",\"doi\":\"10.5167/UZH-132256\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Author name disambiguation (AND) in publication and citation resources is a well-known problem. Often, information about email address and other details in the affiliation is missing. In cases where such information is not available, identifying the authorship of publications becomes very challenging. Consequently, there have been attempts to resolve such cases by utilizing external resources as references. However, such external resources are heterogeneous and are not always reliable regarding the correctness of information. To solve the AND task, especially when information about an author is not complete we suggest the use of new features such as journal descriptors (JD) and semantic types (ST). The evaluation of different feature models shows that their inclusion has an impact equivalent to that of other important features such as email address. Using such features we show that our system outperforms the state of the art.\",\"PeriodicalId\":297051,\"journal\":{\"name\":\"BioTxtM@COLING 2016\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BioTxtM@COLING 2016\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5167/UZH-132256\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BioTxtM@COLING 2016","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5167/UZH-132256","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Author Name Disambiguation in MEDLINE Based on Journal Descriptors and Semantic Types
Author name disambiguation (AND) in publication and citation resources is a well-known problem. Often, information about email address and other details in the affiliation is missing. In cases where such information is not available, identifying the authorship of publications becomes very challenging. Consequently, there have been attempts to resolve such cases by utilizing external resources as references. However, such external resources are heterogeneous and are not always reliable regarding the correctness of information. To solve the AND task, especially when information about an author is not complete we suggest the use of new features such as journal descriptors (JD) and semantic types (ST). The evaluation of different feature models shows that their inclusion has an impact equivalent to that of other important features such as email address. Using such features we show that our system outperforms the state of the art.