Abstract
With the rapid development of social networks and cyber-physical systems, heterogeneous information networks have become increasingly popular. In many cases, such networks contain multiple types of objects and links. In traditional data warehouses and OLAP technique, iceberg cube are those whose aggregated functions are larger than a specific threshold. However traditional iceberg cube analysis techniques cannot be directly applied to graphs for finding interesting cubes due to the lack of structures in graphs. This paper addresses the interesting problem of iceberg cube query on heterogeneous information networks. Based on the intuition, we proposed a cube model based on attribute consistency and link consistency. And the iceberg cubes computation is realized by pruning on the two parts. And random walk is used to aggregate the nodes in heterogeneous information networks for approximate iceberg cubes. Experiments on real world heterogeneous information networks demonstrate the algorithm effective and efficiency.
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Yin, D., Gao, H. (2014). Iceberg Cube Query on Heterogeneous Information Networks. In: Cai, Z., Wang, C., Cheng, S., Wang, H., Gao, H. (eds) Wireless Algorithms, Systems, and Applications. WASA 2014. Lecture Notes in Computer Science, vol 8491. Springer, Cham. https://doi.org/10.1007/978-3-319-07782-6_66
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DOI: https://doi.org/10.1007/978-3-319-07782-6_66
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07781-9
Online ISBN: 978-3-319-07782-6
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