Web Service Mining

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 aim...

Full description

Bibliographic Details
Main Author: Zheng, George
Other Authors: Computer Science
Format: Others
Published: Virginia Tech 2014
Subjects:
Online Access:http://hdl.handle.net/10919/26324
http://scholar.lib.vt.edu/theses/available/etd-02272009-195012/
id ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-26324
record_format oai_dc
spelling ndltd-VTETD-oai-vtechworks.lib.vt.edu-10919-263242020-09-26T05:31:39Z Web Service Mining Zheng, George Computer Science Bouguettaya, Athman Barkhi, Reza Zhang, Liqing Lu, Chang-Tien Gracanin, Denis Web service pathway discovery ontology interestingness service mining 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. Ph. D. 2014-03-14T20:07:50Z 2014-03-14T20:07:50Z 2009-02-04 2009-02-27 2012-04-06 2009-03-30 Dissertation etd-02272009-195012 http://hdl.handle.net/10919/26324 http://scholar.lib.vt.edu/theses/available/etd-02272009-195012/ permissions.doc dissertation_georgezheng.pdf In Copyright http://rightsstatements.org/vocab/InC/1.0/ application/msword application/pdf Virginia Tech
collection NDLTD
format Others
sources NDLTD
topic Web service
pathway discovery
ontology
interestingness
service mining
spellingShingle Web service
pathway discovery
ontology
interestingness
service mining
Zheng, George
Web Service Mining
description 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. === Ph. D.
author2 Computer Science
author_facet Computer Science
Zheng, George
author Zheng, George
author_sort Zheng, George
title Web Service Mining
title_short Web Service Mining
title_full Web Service Mining
title_fullStr Web Service Mining
title_full_unstemmed Web Service Mining
title_sort web service mining
publisher Virginia Tech
publishDate 2014
url http://hdl.handle.net/10919/26324
http://scholar.lib.vt.edu/theses/available/etd-02272009-195012/
work_keys_str_mv AT zhenggeorge webservicemining
_version_ 1719340801992949760