Tree-structured Data Clustering with Graph Edit Distance

Date

2019-06-23

Author

Dinler, Derya
Tural, Mustafa Kemal
Özdemirel, Nur Evin

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https://hdl.handle.net/11511/86375

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Tree-structured Data Clustering Dinler, Derya; Tural, Mustafa Kemal; Özdemirel, Nur Evin (2018-07-08) Traditional clustering techniques deal with point data. However, improving measurement capabilities and the need for deeper analyses result in collecting more complex datasets. In this study, we consider a clustering problem in which the data objects are rooted trees with unweighted or weighted edges. Such tree clustering problems arise inmany areas such as biology, neuroscience and computer or social networks. For the solution of the problem, we propose a k-means based algorithm which starts with initial c...
Tree-structured Data Clustering Dinler, Derya; Tural, Mustafa Kemal; Özdemirel, Nur Evin (null; 2018-07-08) Traditional clustering techniques deal with point data. However, improving measurement capabilities and the need for deeper analyses result in collecting more complex datasets. In this study, we consider a clustering problem in which the data objects are rooted trees with unweighted or weighted edges. Such tree clustering problems arise inmany areas such as biology, neuroscience and computer or social networks. For the solution of the problem, we propose a k-means based algorithm which starts with initial c...
Tree-structured Data Clustering Dinler, Derya; Tural, Mustafa Kemal; Özdemirel, Nur Evin (null; 2018-11-04) Tree-structured Data ClusteringWe consider a clustering problem in which data objects are rooted trees withunweighted or weighted edges and propose a k-means based algorithm whichrepeats assignment and update steps until convergence. The assignment steputilizes Vertex Edge Overlap to assign each data object to the most similarcentroid. In the update step, each centroid is updated by considering the dataobjects assigned to it. For the unweighted edges case, we propose a NonlinearInteger Programming (NIP) for...
Tree-structured Data Clustering Dinler, Derya; Tural, Mustafa Kemal; Özdemirel, Nur Evin (2019-11-04) Tree-structured Data ClusteringWe consider a clustering problem in which data objects are rooted trees withunweighted or weighted edges and propose a k-means based algorithm whichrepeats assignment and update steps until convergence. The assignment steputilizes Vertex Edge Overlap to assign each data object to the most similarcentroid. In the update step, each centroid is updated by considering the dataobjects assigned to it. For the unweighted edges case, we propose a NonlinearInteger Programming (NIP) for...
Image segmentation with unified region and boundary characteristics within recursive shortest spanning tree Esen, E.; Alp, Y. K. (2007-06-13) The lack of boundary information in region based image segmentation algorithms resulted in many hybrid methods that integrate the complementary information sources of region and boundary, in order to increase the segmentation performance. In compliance with this trend, we propose a novel method to unify the region and boundary characteristics within the canonical Recursive Shortest Spanning Tree algorithm. The main idea is to incorporate the boundary information in the distance metric of RSST with minor cha...

Citation Formats

D. Dinler, M. K. Tural, and N. E. Özdemirel, “Tree-structured Data Clustering with Graph Edit Distance,” 2019, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/86375.