کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6856166 | 1437947 | 2018 | 12 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Identifying advisor-advisee relationships from co-author networks via a novel deep model
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Advisor-advisee is one of the most important relationships in research publication networks. Identifying it can benefit many interesting applications, such as double-blind peer review, academic circle mining, and scientific community analysis. However, the advisor-advisee relationships are often hidden in research publication network and vary over time, thus are difficult to detect. In this paper, we present a time-aware Advisor-advisee Relationship Mining Model (tARMM) to better identify such relationships. It is a deep model equipped with improved Refresh Gate Recurrent Units (RGRU). Extensive experiments over real-world DBLP data have well verified the effectiveness of our proposed model.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 466, October 2018, Pages 258-269
Journal: Information Sciences - Volume 466, October 2018, Pages 258-269
نویسندگان
Zhongying Zhao, Wenqiang Liu, Yuhua Qian, Liqiang Nie, Yilong Yin, Yong Zhang,