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Virginia Tech

Web Service Mining

Abstract

dc:description.abstract

In this dissertation, we present a novel approach for Web service mining. Web service mining is a new research discipline. It is different from conventional top down service composition approaches that are driven by specific search criteria. Web service mining starts with no such criteria and aims at the discovery of interesting and useful compositions of existing Web services. Web service mining requires the study of three main research topics: semantic description of Web services, efficient bottom up composition of composable services, and interestingness and usefulness evaluation of composed services. We first propose a Web service ontology to describe and organize the constructs of a Web service. We introduce the concept of Web service operation interface for the description of shared Web service capabilities and use Web service domains for grouping Web service capabilities based on these interfaces. We take clues from how Nature solves the problem of molecular composition and introduce the notion of Web service recognition to help devise efficient bottom up service composition strategies. We introduce several service recognition mechanisms that take advantage of the domain-based categorization of Web service capabilities and ontology-based description of operation semantics. We take clues from the drug discovery process and propose a Web service mining framework to group relevant mining activities into a progression of phases that would lead to the eventual discovery of useful compositions. Based on the composition strategies that are derived from recognition mechanisms, we propose a set of algorithms in the screening phase of the framework to automatically identify leads of service compositions. We propose objective interestingness and usefulness measures in the evaluation phase to narrow down the pool of composition leads for further exploration. To demonstrate the effectiveness of our framework and to address challenges faced by existing biological data representation methodologies, we have applied relevant techniques presented in this dissertation to the field of biological pathway discovery.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Computer Science
Department dc:contributor.department
Computer Science
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2009

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Zheng, George
Chairs dc:contributor.committeechair
  • Bouguettaya, Athman
  • Gracanin, Denis
Committee members dc:contributor.committeemember
  • Barkhi, Reza
  • Zhang, Liqing
  • Lu, Chang-Tien

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-02272009-195012
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/26324

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Zheng, George. Web Service Mining. doctoral thesis, Virginia Tech, 2009. http://hdl.handle.net/10919/26324