Link prediction is an important problem in network data mining, which dedicated to predicting the potential relationship between nodes network. Normally, link based on supervised classification will be trained a dataset consisting of set positive samples and negative samples. However, well-labeled training datasets with annotations are always inadequate real-world scenarios, contain large numbe...

Link prediction (LP) algorithms propose to each node a ranked list of nodes that are currently non-neighbors, as the most likely candidates for future linkage. Owing increasing concerns about privacy, users (nodes) may prefer keep some their connections protected or private. Motivated by this observation, our goal is design differentially private LP algorithm, which trades off between privacy n...

Link prediction, as an important research direction in complicated network analysis, has broad application prospects. However, traditional link prediction algorithms are generally designed by the sparse expression of adjacency matrix, which is computationally expensive and inefficient, being also unable to run on large-scale networks preserve their higher order structural features. To fill this...

Predicting new links in complex networks can have a large societal impact. In fact, many systems be modeled through networks, and the meaning of depend on system itself. For instance, social where nodes are users, represent relationships (such as acquaintance, friendship, etc.), whereas information spreading users content interactions, diffusion, etc. However, while approaches involve machine l...

The incompleteness of Knowledge Graphs (KGs) is a crucial issue affecting the quality AI-based services. In scholarly domain, KGs describing research publications typically lack important information, hindering our ability to analyse and predict dynamics. recent years, link prediction approaches based on Graph Embedding models became first aid for this issue. work, we present Trans4E, novel emb...

Predicting linkages among data objects is a fundamental data mining task in various application domains, including recommender systems, information retrieval, automatic Web hyperlink generation, record linkage, and communication surveillance. In many contexts link prediction is entirely based on the linkage information itself (a prominent example is the collaborative filtering recommendation). ...

Mobile Ad hoc Network (MANET) consists of a group of mobile nodes that can communicate with each other without the need of infrastructure. The movement of nodes in MANET is random; therefore MANETs have a dynamic topology. Because of this dynamic topology, the link breakages in these networks are something common. This problem causes high data loss and delay. In order to decrease these problems...