{"title":"面向特定主题的科学素质","authors":"Hao Wu, Yijian Pei","doi":"10.1109/BMEI.2009.5305784","DOIUrl":null,"url":null,"abstract":"The studies of citations are comprehensively carried out with the increasing electronically citation data on the Web. Most of the metrics observe scientific quality in a global view instead of in multiple fine-grained views. In this paper, we suggest to apply Topic Model and adaptive PageRank algorithm to assess the relative importance of scientific objects including articles, authors, conferences and journals. The scientific quality is measured by an aggregation PageRank metric towards some topics. This metric considers the impact of a paper both in global view and local view. The experiments on ACL Anthology bibliographic corpus show our method is a useful measure to observe scientific quality on multi-views. KeywordsPageRank; Topic Model; Citation Analysis","PeriodicalId":6389,"journal":{"name":"2009 2nd International Conference on Biomedical Engineering and Informatics","volume":"94 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scientific Quality Towards Specific Topics\",\"authors\":\"Hao Wu, Yijian Pei\",\"doi\":\"10.1109/BMEI.2009.5305784\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The studies of citations are comprehensively carried out with the increasing electronically citation data on the Web. Most of the metrics observe scientific quality in a global view instead of in multiple fine-grained views. In this paper, we suggest to apply Topic Model and adaptive PageRank algorithm to assess the relative importance of scientific objects including articles, authors, conferences and journals. The scientific quality is measured by an aggregation PageRank metric towards some topics. This metric considers the impact of a paper both in global view and local view. The experiments on ACL Anthology bibliographic corpus show our method is a useful measure to observe scientific quality on multi-views. KeywordsPageRank; Topic Model; Citation Analysis\",\"PeriodicalId\":6389,\"journal\":{\"name\":\"2009 2nd International Conference on Biomedical Engineering and Informatics\",\"volume\":\"94 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd International Conference on Biomedical Engineering and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BMEI.2009.5305784\",\"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 2nd International Conference on Biomedical Engineering and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEI.2009.5305784","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The studies of citations are comprehensively carried out with the increasing electronically citation data on the Web. Most of the metrics observe scientific quality in a global view instead of in multiple fine-grained views. In this paper, we suggest to apply Topic Model and adaptive PageRank algorithm to assess the relative importance of scientific objects including articles, authors, conferences and journals. The scientific quality is measured by an aggregation PageRank metric towards some topics. This metric considers the impact of a paper both in global view and local view. The experiments on ACL Anthology bibliographic corpus show our method is a useful measure to observe scientific quality on multi-views. KeywordsPageRank; Topic Model; Citation Analysis
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