{"title":"如何识别与研究人员不断变化的兴趣相关的专门研究社区","authors":"Hamed Alhoori","doi":"10.1145/2910896.2925450","DOIUrl":null,"url":null,"abstract":"Scholarly events and venues are increasing rapidly in number. This poses a challenge for researchers who seek to identify events and venues related to their work in order to draw more efficiently and comprehensively from published research and to share their own findings more effectively. Such efforts are hampered also by the fact that no rating system yet exists to assist researchers in culling the venues most relevant to their current readings and interests. This study describes a methodology we developed in response to this need, one that recommends scholarly venues related to researchers' specific interests according to personalized social web indicators. Our experiments applying our proposed rating and recommendation method show that it outperforms the baseline venue recommendations in terms of accuracy and ranking quality.","PeriodicalId":109613,"journal":{"name":"2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"How to identify specialized research communities related to a researcher's changing interests\",\"authors\":\"Hamed Alhoori\",\"doi\":\"10.1145/2910896.2925450\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Scholarly events and venues are increasing rapidly in number. This poses a challenge for researchers who seek to identify events and venues related to their work in order to draw more efficiently and comprehensively from published research and to share their own findings more effectively. Such efforts are hampered also by the fact that no rating system yet exists to assist researchers in culling the venues most relevant to their current readings and interests. This study describes a methodology we developed in response to this need, one that recommends scholarly venues related to researchers' specific interests according to personalized social web indicators. Our experiments applying our proposed rating and recommendation method show that it outperforms the baseline venue recommendations in terms of accuracy and ranking quality.\",\"PeriodicalId\":109613,\"journal\":{\"name\":\"2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL)\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2910896.2925450\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2910896.2925450","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
How to identify specialized research communities related to a researcher's changing interests
Scholarly events and venues are increasing rapidly in number. This poses a challenge for researchers who seek to identify events and venues related to their work in order to draw more efficiently and comprehensively from published research and to share their own findings more effectively. Such efforts are hampered also by the fact that no rating system yet exists to assist researchers in culling the venues most relevant to their current readings and interests. This study describes a methodology we developed in response to this need, one that recommends scholarly venues related to researchers' specific interests according to personalized social web indicators. Our experiments applying our proposed rating and recommendation method show that it outperforms the baseline venue recommendations in terms of accuracy and ranking quality.