Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem
Annals of Operations Research - Special issue on Tabu search
Experiments on using semantic distances between words in image caption retrieval
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
A User-Centered Location Model
Personal and Ubiquitous Computing
Audio Structuring and Personalized Retrieval Using Ontologies
ADL '00 Proceedings of the IEEE Advances in Digital Libraries 2000
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Learning transportation mode from raw gps data for geographic applications on the web
Proceedings of the 17th international conference on World Wide Web
Two hybrid differential evolution algorithms for engineering design optimization
Applied Soft Computing
Digital ants as the best cicerones for museum visitors
Applied Soft Computing
A statistical recommendation model of mobile services based on contextual evidences
Expert Systems with Applications: An International Journal
Predestination: inferring destinations from partial trajectories
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Ant colony system: a cooperative learning approach to the traveling salesman problem
IEEE Transactions on Evolutionary Computation
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
TSACO: extending a context-aware recommendation system with allen temporal operators
UCAmI'12 Proceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence
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Modern technology has brought many changes to our everyday lives. Our need to be in constant touch with others has been met with the cellphone, which has become our companion and the convergence point of many technological advances. The combination of capabilities such as browsing the Internet and GPS reception has multiplied the services and applications based on the current location of the user. However, providing the user with these services has certain drawbacks. Although map navigation systems are the most meaningful way of displaying this information, the user still has to manually set up the filter in order to obtain a non-bloated visualization of the map and the available services. To tackle this problem, we present here a semantic multicriteria ant colony algorithm capable of learning the user's routes, including associated context information, and then predicting the most likely route a user is following, given his current location and context data. This knowledge could then be used as the basis for offering services related to his current (or most likely future) context data close to the path he is following. Our experimental results show that our algorithm is capable of obtaining consistent solutions sets even when multiple objective ontological terms are included in the process.