Performance and Quality Evaluation of a Personalized Route Planning System

Advanced personalization of database applications is a big challenge, in particular for distributed mobile environments. We present several new results from a prototype of a route planning system. We demonstrate how to combine qualitative and quantitative preferences gained from situational aspects and from personal user preferences. For performance studies we analyze the runtime efficiency of the SR-Combine algorithm used to evaluate top-k queries. By determining the cost-ratio of random to sorted accesses SR-Combine can automatically tune its performance within the given system architecture. Top-k queries are generated by mapping linguistic variables to numerical weightings. Moreover, we analyze the quality of the query results by several test series, systematically varying the mappings of the linguistic variables. We report interesting insights into this rather under-researched important topic. More investigations, incorporating also cognitive issues, need to be conducted in the future.