Call for Papers

Driven by technological advances in hardware (positioning systems, environmental sensors), software (standards, tools, network services), and aided by various open movements (open, linked, government data) and the ever-growing mentality of sharing for the greater good (crowdsourcing, crowdfunding, collaborative and volunteered geographic information), the amount of available geo-referenced data has seen dramatic explosion over the past few years. Human activities generate data and traces that are now often transparently annotated with location and contextual information. At the same time, it has become easier than ever to collect and combine rich and diverse information about locations. Exploiting this torrent of geo-referenced data provides a tremendous potential to materially improve existing and offer novel types of recommendation services, with clear benefits in many domains, including social networks, marketing, and tourism.

Fully exploiting this potential requires addressing many core challenges and combining ideas and techniques from various research communities, such as recommender systems, data management, geographic information systems, social network analytics, text mining. Bringing together researchers and practitioners from these communities, the aim of this workshop is to provide a unique forum for discussing in depth and collecting feedback about challenges, opportunities, novel techniques and applications. LocalRec is about making recommendations in which location plays a key role, either as part of the recommended object, or as part of the recommendation process.

We solicit original contributions of both long and short research or survey papers and short vision or demonstration papers addressing the following non-comprehensive list of topics:

Location-aware recommender systems

location as context

collaborative filtering vs. content-based recommendations

case and empirical studies

evaluation methods and metrics; datasets and benchmarks

Location-based social networks

recommendations for locations, events, venues, travel

friend and community suggestions

extracting preferences, tips, ratings, patterns, habits

modeling geo-social influence of users and locations

Location-based advertising

location-aware viral campaigns

proximity marketing; beacons and IoT

Tourism

trip planning and recommendations

recommending travel destinations, hotels

recommending tourist routes and points of interest

automatic guide and tour generation

exhibition arrangement

Security and privacy in location-aware applications

attack and threat scenarios

spatial anonymization and cloaking

Workshop proceedings will be indexed by DBLP and will appear on ACM Digitial Library.