Context-Aware User and Service Profiling by Means of Generalized Association Rules

Author:

Baralis Elena,Cagliero Luca,Cerquitelli Tania,Garza Paolo,Marchetti Marco

Publisher

Springer Berlin Heidelberg

Reference16 articles.

1. Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules in Large Databases. In: Proceedings of the 20th VLDB conference, pp. 487–499 (1994)

2. Baralis, E., Cerquitelli, T., D’Elia, V.: Generalized itemset discovery by means of opportunistic aggregation. Technical report, Politecnico di Torino (2009), https://dbdmg.polito.it/twiki/bin/view/Public/NetworkTrafficAnalysis

3. Goethals, B.: Frequent Pattern Mining Implementations, http://www.adrem.ua.ac.be/~goethals/software

4. Bradley, N.A., Dunlop, M.D.: Toward a multidisciplinary model of context to support context-aware computing. Hum.-Comput. Interact. 20(4), 403–446 (2005)

5. Byun, H., Cheverst, K.: Utilizing context history to provide dynamic adaptations. Applied Artificial Intelligence 18(6), 533–548 (2004)

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