Standard
Toward Unified Cloud Service Discovery for Enhanced Service Identification. / Alfazi, Abdullah; Sheng, Quan Z.
; Babar, Ali et al.
Service Research and Innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Revised Selected Papers. ed. / Amin Beheshti; Wei Emma Zhang; Hai Dong; Mustafa Hashmi. Springer Verlag, 2018. p. 149-163 (Lecture Notes in Business Information Processing; Vol. 234).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Alfazi, A, Sheng, QZ
, Babar, A, Ruan, W & Qin, Y 2018,
Toward Unified Cloud Service Discovery for Enhanced Service Identification. in A Beheshti, WE Zhang, H Dong & M Hashmi (eds),
Service Research and Innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Revised Selected Papers. Lecture Notes in Business Information Processing, vol. 234, Springer Verlag, pp. 149-163, 6th Australasian Symposium on Service Research and Innovation, ASSRI 2017, New South Wales, Australia,
19/10/17.
https://doi.org/10.1007/978-3-319-76587-7_10APA
Alfazi, A., Sheng, Q. Z.
, Babar, A., Ruan, W., & Qin, Y. (2018).
Toward Unified Cloud Service Discovery for Enhanced Service Identification. In A. Beheshti, W. E. Zhang, H. Dong, & M. Hashmi (Eds.),
Service Research and Innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Revised Selected Papers (pp. 149-163). (Lecture Notes in Business Information Processing; Vol. 234). Springer Verlag.
https://doi.org/10.1007/978-3-319-76587-7_10Vancouver
Alfazi A, Sheng QZ
, Babar A, Ruan W, Qin Y.
Toward Unified Cloud Service Discovery for Enhanced Service Identification. In Beheshti A, Zhang WE, Dong H, Hashmi M, editors, Service Research and Innovation: 5th and 6th Australasian Symposium, ASSRI 2015 and ASSRI 2017, Revised Selected Papers. Springer Verlag. 2018. p. 149-163. (Lecture Notes in Business Information Processing). Epub 2018 Mar 3. doi: 10.1007/978-3-319-76587-7_10
Author
Bibtex
@inproceedings{f24e8790adf648d1a65877509d862af2,
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",
month = apr,
day = "1",
doi = "10.1007/978-3-319-76587-7_10",
language = "English",
isbn = "9783319765860",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer Verlag",
pages = "149--163",
editor = "Amin Beheshti and Zhang, {Wei Emma} and Hai Dong and Mustafa Hashmi",
booktitle = "Service Research and Innovation",
address = "Germany",
note = "6th Australasian Symposium on Service Research and Innovation, ASSRI 2017 ; Conference date: 19-10-2017 Through 20-10-2017",
}
RIS
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 - 2018/4/1
Y1 - 2018/4/1
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
U2 - 10.1007/978-3-319-76587-7_10
DO - 10.1007/978-3-319-76587-7_10
M3 - Conference contribution/Paper
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 - Zhang, Wei Emma
A2 - Dong, Hai
A2 - Hashmi, Mustafa
PB - Springer Verlag
T2 - 6th Australasian Symposium on Service Research and Innovation, ASSRI 2017
Y2 - 19 October 2017 through 20 October 2017
ER -
