A contextual group recommender mechanism for location-based service

Lien Fa Lin, Ting Kai Hwang, Yung-Ming Li, Alvin Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

With the increasing popularity of social media and ubiquity of mobile devices, location-based services have become a trending topic in both academia and industry. These services, such as Foursquare and Facebook Places, allow users to search and explore around them. The notion of group recommendation, though new, has started to generate interest. Many scenarios in our daily lives involve others around us, be it friends or family members. Daily activities, such as watching a movie or eating at a restaurant are often done as a group. In an effort to combine location-based service features with recommender system concepts, we propose a group contextual mechanism for venue recommendation. Our research aims to discover and recommend places that may be of high relevance to a group of people. Preference, as well as social influence and context-awareness are considered as core components in our mechanism. Our system provides an efficient and convenient platform to groups for venue discovery, and increases commercial publicity for service providers.

Original languageEnglish
Title of host publication2015 Americas Conference on Information Systems, AMCIS 2015
PublisherAmericas Conference on Information Systems
ISBN (Electronic)9780996683104
StatePublished - Aug 2015
Event21st Americas Conference on Information Systems, AMCIS 2015 - Fajardo, Puerto Rico
Duration: 13 Aug 201515 Aug 2015

Publication series

Name2015 Americas Conference on Information Systems, AMCIS 2015

Conference

Conference21st Americas Conference on Information Systems, AMCIS 2015
Country/TerritoryPuerto Rico
CityFajardo
Period13/08/1515/08/15

Keywords

  • Context-awareness
  • Group recommender systems
  • Location-based service
  • Social influence

Fingerprint

Dive into the research topics of 'A contextual group recommender mechanism for location-based service'. Together they form a unique fingerprint.

Cite this