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A personalized multimodal tourist tour planner
Author(s) -
Damianos Gavalas,
Vlasios Kasapakis,
Charalampos Konstantopoulos,
Grammati Pantziou,
Nikolaos Vathis,
Christos Zaroliagis
Publication year - 2014
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2677972.2677977
Subject(s) - planner , computer science , tourism , point of interest , context (archaeology) , metropolitan area , destinations , dependency (uml) , world wide web , location based service , routing (electronic design automation) , geography , telecommunications , artificial intelligence , computer network , archaeology
Tourists become increasingly dependent on mobile city guides to locate tourist services and retrieve information about nearby points of interest (POIs) when visiting unknown destinations. Although several city guides support the provision of personalized tour recommendations to assist tourists visiting the most interesting attractions, existing tour planners only consider walking tours. Herein, we introduce eCOMPASS, a context-aware mobile application which also considers the option of using public transit for moving around. Far beyond than just providing navigational aid, eCOMPASS incorporates multimodality (i.e. time dependency) within its routing logic aiming at deriving near-optimal sequencing of POIs along recommended tours so as to best utilize time available for sightseeing and minimize waiting time at transit stops. Further advancing the state of the art, eCOMPASS allows users to define arbitrary start/end locations (e.g. the current location of a mobile user) rather than choosing among a fixed set of locations. This paper describes the routing algorithm which comprises the core functionality of eCOMPASS and discusses the implementation details of the mobile application using the metropolitan area of Berlin (Germany) as case study.

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