Cryptocurrency, as a typical application scene of blockchain, has attracted broad interests
from both industrial and academic communities. With its rapid development, the …

Recently, cross-media web video event mining based on heterogeneous information
networks (HIN) has attracted extensive attention. However, each web video is described by …

Heterogeneous information network (HIN) embedding, aiming to project HIN into a low-
dimensional space, has attracted considerable research attention. Most of the existing HIN …

Recent studies have shown that graph mining models are vulnerable to adversarial attacks.
This paper proposes a robust meta network embedding framework, RoMNE, which improves …

Digital media companies typically collect rich data in the form of sequences of online user
activities. Such data is used in various applications, involving tasks ranging from click or …

We study the problem of Network Embedding (NE) for content-rich networks. NE models aim
to learn efficient low-dimensional dense vectors for network vertices which are crucial to …

现有的网络表示学习方法缺少对网络中隐含的深层次信息进行挖掘和利用.
对网络中的潜在信息做进一步挖掘, 提出了潜在的模式结构相似性, 定义了网络结构间的相似度 …

This paper concerns the problem of network embedding (NE), whose aim is to learn a low-
dimensional representation for each node in networks. We shed a new light to solve the …

In this paper, we propose to embed a content‐rich network for the purpose of similarity
searching for a query node. In this network, besides the information of the nodes and edges …

This work focuses on the enrichment of existing Portuguese word embeddings with visual
information in the form of visual embeddings. This information was extracted from images …