Media type: E-Article Title: Semantic client‐side approach for web personalization of SaaS‐based cloud services Contributor: Fan, Haolong; Hussain, Farookh Khadeer; Hussain, Omar Khadeer imprint: Wiley, 2015 Published in: Concurrency and Computation: Practice and Experience Language: English DOI: 10.1002/cpe.3418 ISSN: 1532-0626; 1532-0634 Keywords: Computational Theory and Mathematics ; Computer Networks and Communications ; Computer Science Applications ; Theoretical Computer Science ; Software Origination: Footnote: Description: <jats:title>Summary</jats:title><jats:p>The demand of software as a service (SaaS)‐based services delivering computing resources as on‐demand software is on the rise in the IT industry. However, one of the drawbacks of the existing SaaS services is that they offer limited or no personalization of the services provided according to the users profile. Personalization as mentioned in the literature has been a key driver in the adoption and usage of various applications and in providing better service experience to the users. However, overwhelming majority of such personalized services rely extensively on the server side, without embracing fast‐developing client‐side technologies. In SaaS‐based cloud services, utilizing this technology is necessary considering their limited processing specifications. Approaches have been proposed in the literature that focus on cloud‐based personalization using client‐side technologies but none of them actually address all the different components that are required for a scalable and holistic personalization framework for SaaS‐based cloud services. In this paper, we address this drawback by proposing a user‐focussed personalization framework. Our proposed framework takes advantage of powerful client side browsers to reduce server overheads, ameliorate performance, establish high intelligence and enrich data processing. To validate and demonstrate the applicability of our framework, we build a prototype model and compare its performance against existing approaches using different metrics. Copyright © 2014 John Wiley & Sons, Ltd.</jats:p>