NDLI: Clustering Service Networks with Entity, Attribute, and Link Heterogeneity

Content Provider	IEEE Xplore Digital Library
Author	Yang Zhou Ling Liu Pu, C. Xianqiang Bao Kisung Lee Palanisamy, B. Yigitoglu, E. Qi Zhang
Copyright Year	2015
Description	Author affiliation: Georgia Inst. of Technol., Atlanta, GA, USA (Yang Zhou; Ling Liu; Pu, C.; Xianqiang Bao; Kisung Lee; Yigitoglu, E.; Qi Zhang) \|\| Univ. of Pittsburgh, Pittsburgh, PA, USA (Palanisamy, B.)
Abstract	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.
Starting Page	257
Ending Page	264
File Size	312177
Page Count	8
File Format	PDF
e-ISBN	9781467372725
DOI	10.1109/ICWS.2015.43
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Clustering algorithms Heterogeneous networks Optimization Web services Shape Polynomials Learning systems
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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