Machine Learning and Data Mining in Pattern Recognition by Unknown

Author:Unknown
Language: eng
Format: epub
ISBN: 9783319961330
Publisher: Springer International Publishing

6 Conclusion

Using fuzzy spectral hierarchical clustering, we created overlapping clusters of entities in political contribution networks. Using the additional data provided with the transactions forming the links between individuals in the network, association rule mining found additional discriminatory information for the communities. The resulting rules aid in providing insight into the donation patterns of groups within the data beyond what was readily apparent from the rules found using the dataset in its entirety. While this work relied on Apriori for rule mining as a proof of concept, future work can use more sophisticated algorithms for determining rules as well. Additionally, future work will explore calculating communities using a heterogeneous clustering techniques that includes the additional transaction data such as party of the recipient, district, and others. By accounting for those values directly, it should be possible to better group individuals into communities based on donation patterns.

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