The active badge location system
ACM Transactions on Information Systems (TOIS)
The nature of statistical learning theory
The nature of statistical learning theory
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Modelling both the Context and the User
Personal and Ubiquitous Computing
User Modeling and User-Adapted Interaction
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
What we talk about when we talk about context
Personal and Ubiquitous Computing
Feature selection using linear classifier weights: interaction with classification models
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Consistent Modelling of Users, Devices and Sensors in a Ubiquitous Computing Environment
User Modeling and User-Adapted Interaction
Preface to the Special Issue on User Modeling in Ubiquitous Computing
User Modeling and User-Adapted Interaction
People tracking with anonymous and ID-sensors using Rao-Blackwellised particle filters
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
A hybrid discriminative/generative approach for modeling human activities
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Location-based activity recognition using relational Markov networks
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Learning and recognizing the places we go
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Cyber Assist Project for Ambient Intelligence
Proceedings of the 2007 conference on Advances in Ambient Intelligence
A survey of computational location privacy
Personal and Ubiquitous Computing
Predicting Customer Models Using Behavior-Based Features in Shops
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
Joint learning user's activities and profiles from GPS data
Proceedings of the 2009 International Workshop on Location Based Social Networks
Object relevance weight pattern mining for activity recognition and segmentation
Pervasive and Mobile Computing
An unsupervised approach to activity recognition and segmentation based on object-use fingerprints
Data & Knowledge Engineering
Modeling people's place naming preferences in location sharing
Proceedings of the 12th ACM international conference on Ubiquitous computing
Self-supervised mining of human activity from CGM
PKAW'10 Proceedings of the 11th international conference on Knowledge management and acquisition for smart systems and services
Capturing users' buying activity at Akihabara electric town from twitter
ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume Part II
Self-supervised capturing of users' activities from weblogs
International Journal of Intelligent Information and Database Systems
Big brother knows your friends: on privacy of social communities in pervasive networks
Pervasive'12 Proceedings of the 10th international conference on Pervasive Computing
Inferring social ties in academic networks using short-range wireless communications
Proceedings of the 12th ACM workshop on Workshop on privacy in the electronic society
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Recent development of location technologies enables us to obtain the location history of users. This paper proposes a new method to infer users' longterm properties from their respective location histories. Counting the instances of sensor detection for every user, we can obtain a sensor-user matrix. After generating features from the matrix, a machine learning approach is taken to automatically classify users into different categories for each user property. Inspired by information retrieval research, the problem to infer user properties is reduced to a text categorization problem. We compare weightings of several features and also propose sensor weighting. Our algorithms are evaluated using experimental location data in an office environment.