| Title | An Efficient Hash-Tree-Based Algorithm in Mining Sequential Patterns with Topology Constraint |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Sun, Wenhua, Wang, Xiaojuan, Jin, Lei |
| Conference Name | 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS) |
| Date Published | aug |
| Keywords | alarm association rules, association rules, Business, compositionality, Conferences, data mining, efficient hash-tree-based algorithm, hash algorithms, Hash functions, hash tree, hash tree efficiency, hash-tree based mining, hash-tree search method, Internet, mining efficiency, network nodes, network physical connection data, Network topology, Pattern recognition, pubcrawl, Resiliency, sequential mining algorithm, sequential pattern mining, Sun, telecommunication network topology, Topology, topology constraint, topology relation, topology structure, transmission network, transmission networks, tree searching, trees (mathematics), warning Weblogs |
| Abstract | Warnings happen a lot in real transmission networks. These warnings can affect people's lives. It is significant to analyze the alarm association rules in the network. Many algorithms can help solve this problem but not considering the actual physical significance. Therefore, in this study, we mine the association rules in warning weblogs based on a sequential mining algorithm (GSP) with topology structure. We define a topology constraint from network physical connection data. Under the topology constraint, network nodes have topology relation if they are directly connected or have a common adjacency node. In addition, due to the large amount of data, we implement the hash-tree search method to improve the mining efficiency. The theoretical solution is feasible and the simulation results verify our method. In simulation, the topology constraint improves the accuracy for 86%-96% and decreases the run time greatly at the same time. The hash-tree based mining results show that hash tree efficiency improvements are in 3-30% while the number of patterns remains unchanged. In conclusion, using our method can mine association rules efficiently and accurately in warning weblogs. |
| DOI | 10.1109/HPCC/SmartCity/DSS.2019.00390 |
| Citation Key | sun_efficient_2019 |
An Efficient Hash-Tree-Based Algorithm in Mining Sequential Patterns with Topology Constraint