Modeling people's place naming preferences in location sharing

Most location sharing applications display people's locations on a map. However, people use a rich variety of terms to refer to their locations, such as "home," "Starbucks," or "the bus stop near my house." Our longterm goal is to create a system that can automatically generate appropriate place names based on real-time context and user preferences. As a first step, we analyze data from a two-week study involving 26 participants in two different cities, focusing on how people refer to places in location sharing. We derive a taxonomy of different place naming methods, and show that factors such as a person's perceived familiarity with a place and the entropy of that place (i.e. the variety of people who visit it) strongly influence the way people refer to it when interacting with others. We also present a machine learning model for predicting how people name places. Using our data, this model is able to predict the place naming method people choo...

• Type: Conference
• Year: 2010
• Where: HUC
• Authors: Jialiu Lin, Guang Xiang, Jason I. Hong, Norman M. Sadeh
• Keywords: Applications Display People, HUC 2010, Human Computer Interaction, Location Sharing, Place Naming Method