{"title":"Weak Ties Based Recommendation for Interdisciplinary Research Collaboration","authors":"Won Kyung Lee, S. Sohn","doi":"10.1145/3110025.3120990","DOIUrl":null,"url":null,"abstract":"This study investigates recommendations for interdisciplinary research collaboration based on the weak ties theory. Contents-based features are proposed to recommend interdisciplinary collaboration considering that some researchers who have shown a preference for interdisciplinary collaboration could be connected even if they have dissimilar research profiles. Therefore, we inferred the preference of interdisciplinary research collaboration for every researcher, and considered features such as highlighting dissimilar researchers depending on their preferences. The features are designed to have typical similarity measures when the researchers do not prefer interdisciplinary research collaboration. We evaluated our proposed features with the baseline features of patent application datasets and the former methods outperformed the latter methods.","PeriodicalId":399660,"journal":{"name":"Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3110025.3120990","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study investigates recommendations for interdisciplinary research collaboration based on the weak ties theory. Contents-based features are proposed to recommend interdisciplinary collaboration considering that some researchers who have shown a preference for interdisciplinary collaboration could be connected even if they have dissimilar research profiles. Therefore, we inferred the preference of interdisciplinary research collaboration for every researcher, and considered features such as highlighting dissimilar researchers depending on their preferences. The features are designed to have typical similarity measures when the researchers do not prefer interdisciplinary research collaboration. We evaluated our proposed features with the baseline features of patent application datasets and the former methods outperformed the latter methods.