Toward Unified Cloud Service Discovery for Enhanced Service Identification

Alfazi, Abdullah and Sheng, Quan Z. and Babar, Ali and Ruan, Wenjie and Qin, Yongrui (2018) Toward Unified Cloud Service Discovery for Enhanced Service Identification. In: Service Research and Innovation. Lecture Notes in Business Information Processing . Springer Verlag, AUS, pp. 149-163. ISBN 9783319765860

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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.

Item Type: Contribution in Book/Report/Proceedings
Uncontrolled Keywords: /dk/atira/pure/subjectarea/asjc/1800/1802
Subjects:
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 134227
Deposited By: ep_importer_pure
Deposited On: 22 Jun 2019 00:59
Refereed?: Yes
Published?: Published
Last Modified: 19 Feb 2020 06:44
URI: https://eprints.lancs.ac.uk/id/eprint/134227

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