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Clustering Service Networks with Entity, Attribute, and Link Heterogeneity

Zhou, Y and Liu, L and Pu, C and Bao, X and Lee, K and Palanisamy, B and Yigitoglu, E and Zhang, Q (2015) Clustering Service Networks with Entity, Attribute, and Link Heterogeneity. In: UNSPECIFIED.

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Many popular web service networks are content-rich in terms of heterogeneous types of entities and links, associated with incomplete attributes. Clustering such heterogeneous service networks demands new clustering techniques that can handle two heterogeneity challenges: (1) multiple types of entities co-exist in the same service network with multiple attributes, and (2) links between entities have diverse types and carry different semantics. Existing heterogeneous graph clustering techniques tend to pick initial centroids uniformly at random, specify the number k of clusters in advance, and fix k during the clustering process. In this paper, we propose Service Cluster, a novel heterogeneous service network clustering algorithm with four unique features. First, we incorporate various types of entity, attribute and link information into a unified distance measure. Second, we design a Discrete Steepest Descent method to naturally produce initial k and initial centroids simultaneously. Third, we propose a dynamic learning method to automatically adjust the link weights towards clustering convergence. Fourth, we develop an effective optimization strategy to identify new suitable k and k well-chosen centroids at each clustering iteration. Extensive evaluation on real datasets demonstrates that Service Cluster outperforms existing representative methods in terms of both effectiveness and efficiency.


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Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Zhou, Y
Liu, L
Pu, C
Bao, X
Lee, K
Palanisamy, BBPALAN@pitt.eduBPALAN
Yigitoglu, E
Zhang, Q
Date: 13 August 2015
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Proceedings - 2015 IEEE International Conference on Web Services, ICWS 2015
Page Range: 257 - 264
Event Type: Conference
DOI or Unique Handle: 10.1109/icws.2015.43
Institution: University of Pittsburgh
Refereed: Yes
ISBN: 9781467380904
Date Deposited: 09 Jul 2015 16:06
Last Modified: 30 Mar 2021 13:55


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