Toward unified cloud service discovery for enhanced service identification

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

doi:10.1007/978-3-319-76587-7_10

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

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

1 Citation (Scopus)

Abstract

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 language	English
Title of host publication	Service research and innovation
Subtitle of host publication	5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Sydney, NSW, Australia, November 2–3, 2015, and October 19–20, 2017, Revised selected papers
Editors	Amin Beheshti, Mustafa Hashmi, Hai Dong, Wei Emma Zhang
Place of Publication	Cham
Publisher	Springer, Springer Nature
Pages	149-163
Number of pages	15
ISBN (Electronic)	9783319765877
ISBN (Print)	9783319765860
DOIs	https://doi.org/10.1007/978-3-319-76587-7_10
Publication status	Published - 2018
Event	6th Australasian Symposium on Service Research and Innovation - Sydney, Australia Duration: 19 Oct 2017 → 20 Oct 2017

Publication series

Name	Lecture Notes in Business Information Processing
Volume	234
ISSN (Print)	1865-1348

Conference

Conference	6th Australasian Symposium on Service Research and Innovation
Abbreviated title	ASSRI 2017
Country/Territory	Australia
City	Sydney
Period	19/10/17 → 20/10/17

Keywords

Classification
Cloud service
Service discovery
Service identification

Access to Document

10.1007/978-3-319-76587-7_10

Cite this

Alfazi, A., Sheng, Q. Z., Babar, A., Ruan, W., & Qin, Y. (2018). Toward unified cloud service discovery for enhanced service identification. In A. Beheshti, M. Hashmi, H. Dong, & W. E. Zhang (Eds.), Service research and innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Sydney, NSW, Australia, November 2–3, 2015, and October 19–20, 2017, Revised selected papers (pp. 149-163). (Lecture Notes in Business Information Processing; Vol. 234). Springer, Springer Nature. https://doi.org/10.1007/978-3-319-76587-7_10

Alfazi, Abdullah ; Sheng, Quan Z. ; Babar, Ali ; Ruan, Wenjie ; Qin, Yongrui. / Toward unified cloud service discovery for enhanced service identification. Service research and innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Sydney, NSW, Australia, November 2–3, 2015, and October 19–20, 2017, Revised selected papers. editor / Amin Beheshti ; Mustafa Hashmi ; Hai Dong ; Wei Emma Zhang. Cham : Springer, Springer Nature, 2018. pp. 149-163 (Lecture Notes in Business Information Processing).

@inproceedings{ebeb2ff3eb2940d396fd0fe561e3d394,

title = "Toward unified cloud service discovery for enhanced service identification",

abstract = "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.",

keywords = "Classification, Cloud service, Service discovery, Service identification",

author = "Abdullah Alfazi and Sheng, {Quan Z.} and Ali Babar and Wenjie Ruan and Yongrui Qin",

year = "2018",

doi = "10.1007/978-3-319-76587-7_10",

language = "English",

isbn = "9783319765860",

series = "Lecture Notes in Business Information Processing",

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editor = "Amin Beheshti and Mustafa Hashmi and Hai Dong and Zhang, {Wei Emma}",

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Alfazi, A, Sheng, QZ, Babar, A, Ruan, W & Qin, Y 2018, Toward unified cloud service discovery for enhanced service identification. in A Beheshti, M Hashmi, H Dong & WE Zhang (eds), Service research and innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Sydney, NSW, Australia, November 2–3, 2015, and October 19–20, 2017, Revised selected papers. Lecture Notes in Business Information Processing, vol. 234, Springer, Springer Nature, Cham, pp. 149-163, 6th Australasian Symposium on Service Research and Innovation, Sydney, New South Wales, Australia, 19/10/17. https://doi.org/10.1007/978-3-319-76587-7_10

Toward unified cloud service discovery for enhanced service identification. / Alfazi, Abdullah; Sheng, Quan Z.; Babar, Ali; Ruan, Wenjie; Qin, Yongrui.

Service research and innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Sydney, NSW, Australia, November 2–3, 2015, and October 19–20, 2017, Revised selected papers. ed. / Amin Beheshti; Mustafa Hashmi; Hai Dong; Wei Emma Zhang. Cham : Springer, Springer Nature, 2018. p. 149-163 (Lecture Notes in Business Information Processing; Vol. 234).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution › peer-review

TY - GEN

T1 - Toward unified cloud service discovery for enhanced service identification

AU - Alfazi, Abdullah

AU - Sheng, Quan Z.

AU - Babar, Ali

AU - Ruan, Wenjie

AU - Qin, Yongrui

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - Classification

KW - Cloud service

KW - Service discovery

KW - Service identification

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DO - 10.1007/978-3-319-76587-7_10

M3 - Conference proceeding contribution

AN - SCOPUS:85043576585

SN - 9783319765860

T3 - Lecture Notes in Business Information Processing

SP - 149

EP - 163

BT - Service research and innovation

A2 - Beheshti, Amin

A2 - Hashmi, Mustafa

A2 - Dong, Hai

A2 - Zhang, Wei Emma

PB - Springer, Springer Nature

CY - Cham

T2 - 6th Australasian Symposium on Service Research and Innovation

Y2 - 19 October 2017 through 20 October 2017

ER -

Alfazi A, Sheng QZ, Babar A, Ruan W, Qin Y. Toward unified cloud service discovery for enhanced service identification. In Beheshti A, Hashmi M, Dong H, Zhang WE, editors, Service research and innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Sydney, NSW, Australia, November 2–3, 2015, and October 19–20, 2017, Revised selected papers. Cham: Springer, Springer Nature. 2018. p. 149-163. (Lecture Notes in Business Information Processing). https://doi.org/10.1007/978-3-319-76587-7_10

Toward unified cloud service discovery for enhanced service identification

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Keywords

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