Results 31 to 40 of about 275,529 (157)
Toward an Adaptive Skip-Gram Model for Network Representation Learning
IEEE Access, 2022 The random walk process on network data is a widely-used approach for network representation learning. However, we argue that the sampling of node sequences and the subsampling for the Skip-gram’s contexts have two drawbacks.
I-Chung Hsieh, Cheng-Te Li
doaj +1 more source
Personalized PageRank Graph Attention Networks [PDF]
, 2022 There has been a rising interest in graph neural networks (GNNs) for representation learning over the past few years. GNNs provide a general and efficient framework to learn from graph-structured data.
Choi, Julie
core +1 more source
Entropy, 2023 At present, the existing influence evaluation algorithms often ignore network structure attributes, user interests and the time-varying propagation characteristics of influence.
Zhaohui Li +5 more
doaj +1 more source
Significant Subgraph Detection in Multi-omics Networks for Disease Pathway Identification
Frontiers in Big Data, 2022 Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death in the United States. COPD represents one of many areas of research where identifying complex pathways and networks of interacting biomarkers is an important avenue toward
Mohamed Abdel-Hafiz +10 more
doaj +1 more source
puzzlef/pagerank-adjust-damping-factor: For Adjusting PageRank parameters and Comparing results [v1]
, 2021 Part of the report Adjusting PageRank parameters and Comparing results. Comparing the effect of using different values of damping factor, with PageRank (pull, CSR). Adjustment of the damping factor α is a delicate balancing act. For smaller values of α,
Subhajit Sahu
core +1 more source
, 2013 (15 pages, 6 figures)Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are
Raúl J Mondragón +11 more
core +2 more sources
Search Personalization Based on Social-Network-Based Interestedness Measures
IEEE Access, 2019 Personalized search methods try to tailor the search results to the user's needs and preferences. A popular source of information for personalization is social networks of users.
Shayan A. Tabrizi +3 more
doaj +1 more source
Generalized Erdős numbers for network analysis [PDF]
Royal Society Open Science, 2018 The identification of relationships in complex networks is critical in a variety of scientific contexts. This includes the identification of globally central nodes and analysing the importance of pairwise relationships between nodes.
Greg Morrison +2 more
doaj +1 more source
Graph Neural Network Enhancement Based on Personalized PageRank Higher Order Neighborhood Aggregation [PDF]
Jisuanji gongchengThe key idea behind Graph Neural Network (GNN) is to learn the information representation of a target node by aggregating neighborhood information through the topology of a graph; however, edges that are not relevant to a downstream task or nodes with ...
SHANG Yaming, WU Anbiao, YUAN Ye, WANG Yishu
doaj +1 more source
A time-aware query-focused summarization of an evolving microblogging stream via sentence extraction
Digital Communications and Networks, 2020 With the number of social media users ramping up, microblogs are generated and shared at record levels. The high momentum and large volumes of short texts bring redundancies and noises, in which the users and analysts often find it problematic to elicit ...
Fei Geng, Qilie Liu, Ping Zhang
doaj +1 more source