Abstract
A location-aware news feed system enables mobile users to share geo-tagged user-generated messages, e.g., a user can receive nearby messages that are the most relevant to her. In this paper, we present MobiFeed that is a framework designed for scheduling news feeds for mobile users. MobiFeed consists of three key functions, location prediction, relevance measure, and news feed scheduler. The location prediction function is designed to predict a mobile user's locations based on an existing path prediction algorithm. The relevance measure function is implemented by combining the vector space model with non-spatial and spatial factors to determine the relevance of a message to a user. The news feed scheduler works with the other two functions to generate news feeds for a mobile user at her current and predicted locations with the best overall quality. To ensure that MobiFeed can scale up to a larger number of messages, we design a heuristic news feed scheduler. © 2012 Authors.
| Original language | English |
|---|---|
| Title of host publication | GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems |
| Pages | 538-541 |
| DOIs | |
| Publication status | Published - 2012 |
| Event | 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012 - Redondo Beach, CA, United States Duration: 6 Nov 2012 → 9 Nov 2012 |
Conference
| Conference | 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2012 |
|---|---|
| Country/Territory | United States |
| City | Redondo Beach, CA |
| Period | 6/11/12 → 9/11/12 |
Research Keywords
- location-aware social networks
- mobile computing
- news feed
- online scheduling
