TSACO: Extending a context-aware recommendation system with Allen temporal operators
| Autor: | Jose A. Mocholi, Kamil Krynicki, Alejandro Catala, Javier Jaen |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
ACO
Information retrieval Basis (linear algebra) Context-awareness Computer science business.industry Ant colony optimization algorithms Context (language use) Recommender system Machine learning computer.software_genre Order (business) Path (graph theory) Artificial intelligence Temporal Operators business computer LENGUAJES Y SISTEMAS INFORMATICOS Semantic Search |
| Zdroj: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname Ubiquitous Computing and Ambient Intelligence ISBN: 9783642353765 UCAmI |
| DOI: | 10.1007/978-3-642-35377-2_35 |
| Popis: | In this paper we present our research to extend a recommender system based on a semantic multicriteria ant colony algorithm to allow the use of Allen temporal operators. The system utilizes user’s learnt routes, including their associated context information, in order to predict the most likely route a user is following, given his current location and context data. The addition of temporal operators will increase the level of expressiveness of the queries the system can answer what will allow, in turn, more fine-tuned predictions. This more refined knowledge could then be used as the basis for offering services related to his current (or most likely future) context in the vicinity of the path the user is following This work has been supported by the Centre for the Development of Industrial Technology (CDTI) under the funding project CENIT-MIO! CENIT-2008 1019. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|