Title | ||
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Content Sharing Prediction for Device-to-Device (D2D)-based Offline Mobile Social Networks by Network Representation Learning. |
Abstract | ||
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With the explosion of cellular data, the content sharing in proximity among offline Mobile Social Networks (MSNs) has received significant attention. It is necessary to understand the face-to-face (e.g. Device-to-Device, D2D) social network structure and to predict content propagation precisely, which can be conducted by learning the low-dimensional embedding of the network nodes, called Network Representation Learning (NRL). However, most existing NRL models consider each edge as a binary or continuous value, neglecting rich information between nodes. Besides, many traditional models are almost based on small-scale datasets or online Internet services, severely confining their applications in D2D scenarios. Therefore, we propose ResNel, a RESCAL-based network representation learning model, which aims to regard the multi-dimensional relations as a probability in third-order (3D) tensor space and achieve more accurate predictions for both discovered and undiscovered relations in the D2D social network. Specifically, we consider the Global Positioning System (GPS) information as a critical relation slice to avoid the loss of potential information. Experiments on a realistic large-scale D2D dataset corroborate the advantages of improving forecast accuracy. |
Year | DOI | Venue |
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2020 | 10.1007/978-3-030-60259-8_9 | Interational Conference on Web-Age Information Management |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Qing Zhang | 1 | 0 | 0.34 |
Xiaoxu Ren | 2 | 0 | 0.34 |
Yifan Cao | 3 | 0 | 0.34 |
Hengda Zhang | 4 | 0 | 0.34 |
Xiaofei Wang | 5 | 686 | 58.88 |
Victor C. M. Leung | 6 | 9717 | 759.02 |