Layout as a Service (LaaS): A Service Platform for Self-Optimizing Web Layouts
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Date
2020-01-01
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Language
en
Pages
8
19-26
19-26
Series
Web Engineering - 20th International Conference, ICWE 2020, Proceedings, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 12128 LNCS
Abstract
To personalize a web page, case-specific rules or templates must be specified that define the visuospatial layout of elements as well as device-specific adaptation rules for an individual. This approach scales poorly. We present LaaS, a service platform for self-optimizing web layouts to improve their usability at individual, group, and population levels. No hand-coded rules or templates are needed, as LaaS uses combinatorial optimization to generate web layouts for stated design objectives. This allows personalization to be controlled via intuitive objectives that affect the full web layout. We present an extensible architecture and solutions for (1) layout generation using integer programming, (2) data abstractions to mediate between browsers and layout generators, and (3) page restructuring. Moreover, we show how LaaS can be easily deployed as part of existing web pages. Results demonstrate that our approach can produce usable personalized web layouts in diverse scenarios.Description
Keywords
Self-adaptive web interfaces, Web layouts, Web personalization, Web service architectures, Web-based interaction
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Citation
Laine , M , Nakajima , A , Dayama , N & Oulasvirta , A 2020 , Layout as a Service (LaaS): A Service Platform for Self-Optimizing Web Layouts . in M Bielikova , T Mikkonen & C Pautasso (eds) , Web Engineering - 20th International Conference, ICWE 2020, Proceedings . Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 12128 LNCS , Springer , pp. 19-26 , International Conference on Web Engineering , Helsinki , Finland , 09/06/2020 . https://doi.org/10.1007/978-3-030-50578-3_2
