J. Reyes-Ortíz, Maricela Claudia Bravo, Omar E. Padilla
{"title":"基于短语的语义文本相似度链接研究","authors":"J. Reyes-Ortíz, Maricela Claudia Bravo, Omar E. Padilla","doi":"10.1109/DEXA.2015.54","DOIUrl":null,"url":null,"abstract":"Researchers need to establish networks with colleagues that work similar topics, frequently, they are looking similar works by exploring free text in scientific publications in order to update them with the recent state of the art. They read the abstracts and decide whether or not it is a related and relevant work. Therefore, this paper presents an approach for linking researchers based on measuring the similarity between the abstracts of their scientific publications in English. Our approach discovers ontological relationships between free text scientific publications using statistical and semantic similarity measures. An evaluation of a gold standard data set is presented, it has shown an average of 0.6399 for Pearson product-moment correlation coefficient.","PeriodicalId":239815,"journal":{"name":"2015 26th International Workshop on Database and Expert Systems Applications (DEXA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Phrase-Based Semantic Textual Similarity for Linking Researchers\",\"authors\":\"J. Reyes-Ortíz, Maricela Claudia Bravo, Omar E. Padilla\",\"doi\":\"10.1109/DEXA.2015.54\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Researchers need to establish networks with colleagues that work similar topics, frequently, they are looking similar works by exploring free text in scientific publications in order to update them with the recent state of the art. They read the abstracts and decide whether or not it is a related and relevant work. Therefore, this paper presents an approach for linking researchers based on measuring the similarity between the abstracts of their scientific publications in English. Our approach discovers ontological relationships between free text scientific publications using statistical and semantic similarity measures. An evaluation of a gold standard data set is presented, it has shown an average of 0.6399 for Pearson product-moment correlation coefficient.\",\"PeriodicalId\":239815,\"journal\":{\"name\":\"2015 26th International Workshop on Database and Expert Systems Applications (DEXA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 26th International Workshop on Database and Expert Systems Applications (DEXA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DEXA.2015.54\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 26th International Workshop on Database and Expert Systems Applications (DEXA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEXA.2015.54","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Phrase-Based Semantic Textual Similarity for Linking Researchers
Researchers need to establish networks with colleagues that work similar topics, frequently, they are looking similar works by exploring free text in scientific publications in order to update them with the recent state of the art. They read the abstracts and decide whether or not it is a related and relevant work. Therefore, this paper presents an approach for linking researchers based on measuring the similarity between the abstracts of their scientific publications in English. Our approach discovers ontological relationships between free text scientific publications using statistical and semantic similarity measures. An evaluation of a gold standard data set is presented, it has shown an average of 0.6399 for Pearson product-moment correlation coefficient.