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Ranking Significant Ubiquitous Computing Trails
BibTeX
@MISC{Papadogkonas_rankingsignificant,
author = {Dikaios Papadogkonas and George Roussos and Mark Levene},
title = {Ranking Significant Ubiquitous Computing Trails},
year = {}
}
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Abstract
Trails have been identified as a useful mechanism to provide navigational assistance in ubiquitous computing environments. Indeed, trails provide within a single framework an effective way to record, structure and represent interactions between users and physical or digital resources. Yet, this approach faces several challenges before it becomes practical at large scale since trailbased navigation requires considerable storage and computational resources when carried out naively. In this poster, we propose new methods and techniques that can effectively address these performance considerations and can support processing of large numbers of recorded trails. In particular, we present a stochastic model for the representation of trails and trail aggregates, and suitable data structures for efficient storage, filtering and retrieval which result in significantly improved performance. Furthermore, we propose algorithms and associated metrics that we use to rank trails and identify significant ones. Such significant trails can be subsequently used to guide search and navigation. We conclude by illustrating the use of these techniques in the context of three case studies.
Keyphrases
significant ubiquitous computing trail computational resource new method digital resource associated metric large number trail aggregate several challenge navigational assistance useful mechanism stochastic model case study suitable data structure efficient storage performance consideration significant trail effective way large scale considerable storage single framework represent interaction significant one
