- Title
- DEFINE: friendship detection based on node enhancement
- Creator
- Pan, Hanxiao; Guo, Teng; Bedru, Hayat; Qing, Qing; Zhang, Dongyu; Xia, Feng
- Date
- 2020
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/171720
- Identifier
- vital:14395
- Identifier
-
https://doi.org/10.1007/978-3-030-39469-1_7
- Identifier
- ISBN:0302-9743 (ISSN); 9783030394684 (ISBN)
- Abstract
- Network representation learning (NRL) is a matter of importance to a variety of tasks such as link prediction. Learning low-dimensional vector representations for node enhancement based on nodes attributes and network structures can improve link prediction performance. Node attributes are important factors in forming networks, like psychological factors and appearance features affecting friendship networks. However, little to no work has detected friendship using the NRL technique, which combines students’ psychological features and perceived traits based on facial appearance. In this paper, we propose a framework named DEFINE (No enhancement based r e dship D tection) to detect students’ friend relationships, which combines with students’ psychological factors and facial perception information. To detect friend relationships accurately, DEFINE uses the NRL technique, which considers network structure and the additional attributes information for nodes. DEFINE transforms them into low-dimensional vector spaces while preserving the inherent properties of the friendship network. Experimental results on real-world friendship network datasets illustrate that DEFINE outperforms other state-of-art methods. © 2020, Springer Nature Switzerland AG.; E1
- Publisher
- Springer
- Relation
- 31st Australasian Database Conference, ADC 2019 Vol. 12008 LNCS, p. 81-92
- Rights
- Springer Nature Switzerland AG 2020
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Friendship detection; Node enhancement; Social network
- Full Text
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