Leveraging Incrementally Enriched Domain Knowledge to Enhance Service Categorization-Reference-Cited by-同舟云学术

Leveraging Incrementally Enriched Domain Knowledge to Enhance Service Categorization

Published:2012-07 Issue:3 Volume:9 Page:43-66
ISSN:1545-7362
Container-title:International Journal of Web Services Research
language:en
Short-container-title:

Author:

Zhang Jia¹,Wang Jian²,Hung Patrick³,Li Zheng²,Zhang Neng²,He Keqing²

Affiliation:

1. Carnegie Mellon University, Silicon Valley, USA

2. State Key Lab of Software Engineering, Computer School, Wuhan University, China

3. University of Ontario Institute of Technology, Canada

Abstract

This paper reports the authors’ study over an open service and mashup repository, ProgrammableWeb, which groups stored services into predefined categories. Leveraging such a unique structural feature and hidden domain knowledge of the service repository, they extend the Support Vector Machine (SVM)-based text classification technique to enhance service-oriented categorization. An iterative approach is presented to automatically verify and adjust service categorization, which will incrementally enrich domain ontology and in turn enhance the accuracy of service categorization.

Publisher

IGI Global

Subject

Computer Networks and Communications,Information Systems,Software

Reference40 articles.

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