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.
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Laine, M., Nakajima, A., Dayama, N., Oulasvirta, A. (2020). Layout as a Service (LaaS): A Service Platform for Self-Optimizing Web Layouts. In: Bielikova, M., Mikkonen, T., Pautasso, C. (eds) Web Engineering. ICWE 2020. Lecture Notes in Computer Science(), vol 12128. Springer, Cham. https://doi.org/10.1007/978-3-030-50578-3_2
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DOI: https://doi.org/10.1007/978-3-030-50578-3_2
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