Ruben Verborgh’s data

Matches in Ruben’s data for { <https://ruben.verborgh.org/publications/delva_sem4tra_2020/#publication> ?p ?o }

• publication author me.
• publication author pieter_ballon.
• publication author harm_delva.
• publication author annelien_smets.
• publication author me.
• publication creator me.
• publication creator pieter_ballon.
• publication creator harm_delva.
• publication creator annelien_smets.
• publication creator me.
• publication about proof.
• publication about World_Wide_Web.
• publication author me.
• publication author pieter_ballon.
• publication author harm_delva.
• publication author annelien_smets.
• publication author me.
• publication coparticipatesWith me.
• publication coparticipatesWith pieter_ballon.
• publication coparticipatesWith harm_delva.
• publication coparticipatesWith annelien_smets.
• publication coparticipatesWith me.
• publication type ScholarlyArticle.
• publication type Article.
• publication type Document.
• publication type Document.
• publication type Document.
• publication type Q386724.
• publication type CreativeWork.
• publication type Work.
• publication P50 me.
• publication P50 pieter_ballon.
• publication P50 harm_delva.
• publication P50 annelien_smets.
• publication P50 me.
• publication maker me.
• publication maker pieter_ballon.
• publication maker harm_delva.
• publication maker annelien_smets.
• publication maker me.
• publication title "Using Regions of Interest for Personalized Route Planning".
• publication isPartOf proceedings_of_the_2nd_international_workshop_on_semantics_for_transport.
• publication name "Using Regions of Interest for Personalized Route Planning".
• publication label "Using Regions of Interest for Personalized Route Planning".
• publication name "Using Regions of Interest for Personalized Route Planning".
• publication topic proof.
• publication topic World_Wide_Web.
• publication subject proof.
• publication subject World_Wide_Web.
• publication authorList b0_b1882.
• publication topic proof.
• publication topic World_Wide_Web.
• publication abstract "There is an abundance of services and applications that find the most efficient route between two places, but people are not always interested in efficiency; sometimes we just want a pleasant route. Such routes are subjective though, and may depend on contextual factors that route planners are oblivious to. One possible solution is to automatically learn what a user wants, but this requires behavioral data, leading to a cold start problem. Moreover, this approach falls flat when someone wants to try something new, as users become locked in filter bubbles. An alternative approach is to let the user express their desires explicitly, effectively helping them create the most pleasant route themselves. In this paper we provide a proof of concept of a client-side route planner that does exactly that. We aggregated the Point of Interest information from OpenStreetMap into Regions of Interest, and published the results on the Web. These regions are described semantically, enabling the route planner to align the user’s input to what is known about their environment. Planning a 3km long pedestrian route through a city center takes 5 seconds, but subsequent adjustments to the route require less than a second to compute. These execution times imply that our approach is feasible, although further optimizations are needed to bring this to the general public.".
• publication datePublished "2020".
• publication mainEntityOfPage delva_sem4tra_2020.
• publication sameAs publication.
• publication isPrimaryTopicOf delva_sem4tra_2020.
• publication page delva_sem4tra_2020.