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abstract: Skyline queries are a well-established technique used in multi criteria decision applications. There is a recent interest among the research community to efficiently compute skylines but the problem of presenting the skyline that takes into account the preferences of the user is still open. Each user has varying interests towards each attribute and hence "one size fits all" methodology might not satisfy all the users. True user satisfaction can be obtained only when the skyline is tailored specifically for each user based on his preferences. This research investigates the problem of preference aware skyline processing which consists of inferring the preferences of users and computing a skyline specific to that user, taking into account his preferences. This research proposes a model that transforms the data from a given space to a user preferential space where each attribute represents the preference of the user. This study proposes two techniques "Preferential Skyline Processing" and "Latent Skyline Processing" to efficiently compute preference aware skylines in the user preferential space. Finally, through extensive experiments and performance analysis the correctness of the recommendations and the algorithm's ability to outperform the naïve ones is confirmed. / Dissertation/Thesis / Masters Thesis Computer Science 2014

Kontextmedvetna spel låter den reella omgivningenpåverka aspekter av spelinnehållet. Då kontextmedvetna spel i en mobil miljö är ett väl utforskat område saknas forskning kring dess möjlighet att även fungera i en stationär miljö. I denna utforskande studie har en modifikation till det stationära spelet Cities: Skylines utvecklats som låter spelarens aktivitet påverka nästkommande spelsession. Modifikationen har sedan använts vid en användarstudie som undersökt hur denna typ av mer löst kopplade kontext där spel och kontext är tidsmässigt separerade påverkar spelarens upplevelse. Studien visar att denna typ av kontextmedvetenhet upplevs önskvärt. Det kan dock krävas någon form av hjälpande länk som förstärker kopplingen mellan spel och kontext samt att kontextmedvetenhetens syfte bör vara att förstärka spelupplevelsen snarare än att vara en drivande faktor.

How can we predict key decisions made by organizations in the presence of big data and on-demand information? In this dissertation we exploit a large repository of B2B real-time transactional data with service quality indicators and present evidence that organizational decision analytics apply both rational and boundedly-rational (i.e. behavioral) economic models. The dissertation’s findings demonstrate that both utility and heuristic models, respectively, play significant roles in predicting organizational decisions on churn, a key decision in this context. In the presence of a large data set the assumed rationality of organizations appears to provide accurate predictions in uncontrolled experiences and selected boundedly-rational decision rules appear to cause somatic states that make organizations more sensitive to past total qualities of service. This dissertation makes significant new contributions to the understanding of how organizations can effectively use big data to make key operational decisions. As a managerial implication, organizations must be alert to heuristics that might exacerbate the impact of total service pain on customer’s decision to churn.