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Data"],"published-print":{"date-parts":[[2021,6,30]]},"abstract":"<jats:p>While scientific collaboration is critical for a scholar, some collaborators can be more significant than others, e.g., lifetime collaborators. It has been shown that lifetime collaborators are more influential on a scholar\u2019s academic performance. However, little research has been done on investigating predicting such special relationships in academic networks. To this end, we propose Scholar2vec, a novel neural network embedding for representing scholar profiles. First, our approach creates scholars\u2019 research interest vector from textual information, such as demographics, research, and influence. After bridging research interests with a collaboration network, vector representations of scholars can be gained with graph learning. Meanwhile, since scholars are occupied with various attributes, we propose to incorporate four types of scholar attributes for learning scholar vectors. Finally, the early-stage similarity sequence based on Scholar2vec is used to predict lifetime collaborators with machine learning methods. Extensive experiments on two real-world datasets show that Scholar2vec outperforms state-of-the-art methods in lifetime collaborator prediction. Our work presents a new way to measure the similarity between two scholars by vector representation, which tackles the knowledge between network embedding and academic relationship mining.<\/jats:p>","DOI":"10.1145\/3442199","type":"journal-article","created":{"date-parts":[[2021,4,21]],"date-time":"2021-04-21T15:42:54Z","timestamp":1619019774000},"page":"1-19","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Scholar2vec: Vector Representation of Scholars for Lifetime Collaborator Prediction"],"prefix":"10.1145","volume":"15","author":[{"given":"Wei","family":"Wang","sequence":"first","affiliation":[{"name":"Dalian University of Technology and University of Macau, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8324-1859","authenticated-orcid":false,"given":"Feng","family":"Xia","sequence":"additional","affiliation":[{"name":"Federation University Australia and Dalian University of Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Wu","sequence":"additional","affiliation":[{"name":"Old Dominion University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiguo","family":"Gong","sequence":"additional","affiliation":[{"name":"University of Macau, Macau, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanghang","family":"Tong","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, Champaign, IL"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9326-3648","authenticated-orcid":false,"given":"Brian D.","family":"Davison","sequence":"additional","affiliation":[{"name":"Lehigh University, Bethlehem, PA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2021,4,21]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11192-017-2599-0"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1998076.1998121"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1510820113"},{"key":"e_1_2_1_5_1","volume-title":"Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies","volume":"1","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin , Ming-Wei Chang , Kenton Lee , and Kristina Toutanova . 2018 . 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