Semantic Traffic-Aware Routing Using the LarKC Platform

Authors:
Emanuele Della Valle;Irene Celino;Daniele Dell'Aglio;Ralph Grothmann;Florian Steinke;Volker Tresp
Affiliations:
Politecnico di Milano;Cefriel, Politecnico di Milano;Cefriel, Politecnico di Milano;Siemens Corporate Research and Technologies;Siemens Corporate Research and Technologies;Siemens Corporate Research and Technologies
Venue:
IEEE Internet Computing
Year:
2011

Citing 0
Cited 4

Linking smart cities datasets with human computation: the case of urbanmatch

ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part II
Applying semantic web technologies for diagnosing road traffic congestions

ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part II
Westland row why so slow?: fusing social media and linked data sources for understanding real-time traffic conditions

Proceedings of the 2013 international conference on Intelligent user interfaces
Building linked ontologies with high precision using subclass mapping discovery

Artificial Intelligence Review

Quantified Score

Hi-index	0.04

Visualization

Abstract

The popularity of location-based services and automotive navigation systems calls for a new generation of intelligent solutions to support users in mobility. This article presents a traffic-aware semantic routing service for mobile users based on the Large Knowledge Collider (LarKC) Semantic Web pluggable platform. It proposes a technique for integrating conceptual query answering with statistical learning and operations research algorithms. The presented prototype of a traffic-aware semantic routing service works efficiently with large, heterogeneous information sources and delivers value-added services to mobile users.