Incorporating weather updates for public transportation users of recommendation systems

Muhammed Mas Ud Hussain*, Besim Avci, Goce Trajcevski, Peter Scheuermann

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

This work presents a system for augmenting the functionality of Yelp-like recommendation sites by enabling users to search for places bounded by travel-time when using public transportation, and modifying recommendations based on updated weather conditions. Using public transport, although is cheaper and efficient, entails that only fixed places of boarding/exiting may be used which, in turn, implies walking to (from) a particular location from (to) a given station. Given the impact of the weather on the mood and activities, preferences for a certain type of services may need to be dynamically adjusted based on the current weather or the near-future forecast, modulo travel-routes to preferred locations. In this work, we develop a model to predict a user's preferred mode of transport (car, or public transit) from their old check-ins and incorporate the weather context into the recommendation process. We use event-based modeling to control the extent of walking depending on user-defined tolerance information and live weather conditions. We implemented a web application (both desktop and mobile platforms), utilizing existing tools such as Google Maps Direction API and Open Weather Map API for retrieving real-time information.

Original languageEnglish (US)
Title of host publicationProceedings - 2016 IEEE 17th International Conference on Mobile Data Management, IEEE MDM 2016
EditorsPrem Jayaraman, Wei Wu, Chi-Yin Chow
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages333-336
Number of pages4
ISBN (Electronic)9781509008834
DOIs
StatePublished - Jul 20 2016
Event17th IEEE International Conference on Mobile Data Management, IEEE MDM 2016 - Porto, Portugal
Duration: Jun 13 2016Jun 16 2016

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
Volume2016-July
ISSN (Print)1551-6245

Other

Other17th IEEE International Conference on Mobile Data Management, IEEE MDM 2016
Country/TerritoryPortugal
CityPorto
Period6/13/166/16/16

Keywords

  • Context-aware Recommendation Systems
  • Location Context
  • Public Transit
  • Unsupervised Learning
  • Weather Context

ASJC Scopus subject areas

  • Engineering(all)

Fingerprint

Dive into the research topics of 'Incorporating weather updates for public transportation users of recommendation systems'. Together they form a unique fingerprint.

Cite this