Toward unified cloud service discovery for enhanced service identification

Abdullah Alfazi*, Quan Z. Sheng, Ali Babar, Wenjie Ruan, Yongrui Qin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

1 Citation (Scopus)


Nowadays cloud services are being increasingly used by professionals. A wide variety of cloud services are being introduced every day, and each of which is designed to serve a set of specific purposes. Currently, there is no cloud service specific search engine or a comprehensive directory that is available online. Therefore, cloud service customers mainly select cloud services based on the word of mouth, which is of low accuracy and lacks expressiveness. In this paper, we propose a comprehensive cloud service search engine to enable users to perform personalized search based on certain criteria including their own intention of use, cost and the features provided. Specifically, our cloud service search engine focuses on: (1) extracting and identifying cloud services automatically from the Web; (2) building a unified model to represent the cloud service features; and (3) prototyping a search engine for online cloud services. To this end, we propose a novel Service Detection and Tracking (SDT) model for modeling Cloud services. Then based on the SDT model, a cloud service search engine (CSSE) is implemented for helping effectively discover cloud services, relevant service features and service costs that are provided by the cloud service providers.

Original languageEnglish
Title of host publicationService research and innovation
Subtitle of host publication5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Sydney, NSW, Australia, November 2–3, 2015, and October 19–20, 2017, Revised selected papers
EditorsAmin Beheshti, Mustafa Hashmi, Hai Dong, Wei Emma Zhang
Place of PublicationCham
PublisherSpringer, Springer Nature
Number of pages15
ISBN (Electronic)9783319765877
ISBN (Print)9783319765860
Publication statusPublished - 2018
Event6th Australasian Symposium on Service Research and Innovation - Sydney, Australia
Duration: 19 Oct 201720 Oct 2017

Publication series

NameLecture Notes in Business Information Processing
ISSN (Print)1865-1348


Conference6th Australasian Symposium on Service Research and Innovation
Abbreviated titleASSRI 2017


  • Classification
  • Cloud service
  • Service discovery
  • Service identification


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