Spatiotemporal movement pattern discovery has stimulated considerable interest due to its numerous applications, including data analysis, machine learning, data segmentation, data …
Uncertain data has posed a great challenge to traditional clustering algorithms. Recently, several algorithms have been proposed for clustering uncertain data, and among them …
Z Halim, JH Khattak - Evolving systems, 2019 - Springer
Clustering is a machine learning task to group similar objects in coherent sets. These groups exhibit similar behavior with-in their cluster. With the exponential increase in the data …
Distance measure plays an important role in clustering uncertain data. However, existing distance measures for clustering uncertain data suffer from some issues. Geometric distance …
Possible world has become one of the most effective tools to deal with various types of data uncertainty in uncertain data management. However, few uncertain data classification …
M Li, X Jin, C Guo, J Liu, G Cui, T Qiu - Knowledge-Based Systems, 2019 - Elsevier
In peer-to-peer service networks, autonomous agents gain utilities through getting services from others. However, providing services is so costly that rational agents may prefer to defect …
X Jin, M Li, Z Wang, C Guo, H Ding… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
There exist two severe challenges in cloud file-sharing networks: cooperation dilemma and trust dilemma. The mechanism designed to promote cooperation could suffer from malicious …
In this thesis, we focus on structural clustering of probabilistic graphs, which comes with significant computational challenges and has, so far, resisted efficient solutions that are able …
X Zhang, L Gao, H Yu - Advances in Knowledge Discovery and Data …, 2016 - Springer
Both uncertain data and high-dimensional data pose huge challenges to traditional clustering algorithms. It is even more challenging for clustering high dimensional uncertain …