A Folksonomy-Based Recommendation System for the Sensor Web

Lecture Notes in Computer Science, 2011, Volume 6574/2011, 64-77

Rohana Rezel and Steve Liang

“This paper introduces a folksonomy-based recommendation system for the worldwide Sensor Web which aims to aid users to deal with the terabytes of data that are generated by the sensors. We demonstrate how folksonomies could be adopted for the Sensor Web and other geospatial applications dealing with large volumes of data, by exploiting the geospatial information associated with three key components of such collaborative tagging systems: tags, resources and users. We propose algorithms for: i) suggesting tags for users during the tag input stage; ii) generating tag maps which provides for serendipitous browsing; and iii) personalized searching within the folksonomy. We experimentally evaluate our algorithms using an existing large dataset. An implementation of the folksonomy for the emerging Sensor Web platform is also presented.”