Implementation of context prediction system based on event recurrence time

Noilas, A., Scellato, S., Lathia, N., Mascolo, C.: Mining user mobility features for next place prediction in location-based services. In: Proceedings of IEEE Data Mining (2012)

Meeyeon, L., Changgyyu, B., Jung-Won, L.: A prediction and auto-execution system of smartphone application services based on user context-awareness. J. Syst. Arch. 60(8), 702–710 (2014)

Kyoungmi, I.: A design of context-prediction structure based on correlation coefficient weight for user’s location awareness. Ph.D thesis of Kongju National University (2011)

Seung-Chul, L.: Solving the ambiguity of an intention reasoning using context-awareness architecture based on ontology. J. Internet Comput. Serv. 8(5), 99–108 (2007)

Shawky, A., Olsen, R., Pedersen, J., Schwefel, H.: Network aware dynamic context subscription management. J. Comput. Netw. 58(15), 239–253 (2014)

Sunyoung, L., Kun Chang, L.: Context-prediction performance by a dynamic Bayesian network: emphasis on location prediction in ubiquitous decision support environment. J. Expert Syst. Appl. 39(5), 4908–4914 (2012)

Yong Hun, K.: An inhabitant location prediction algorithm in a context-aware environment. Master Thesis of Yonsei University (2006)

Behrends, E.: Introduction to Markov Chains: With Special Emphasis on Rapid Mixing. Advanced Lectures in Mathematics. Springer Fachmedien Wiesbaden (2000)

Gurney, K.: An Introduction to Neural Networks. Routledge, London (2002)

Jensen, F.V.: An Introduction to Bayesian Networks. UCL Press, London (1996)

Han, J.J.: A context-aware service model using a multi-level prediction algorithm in smart home environments. Master Thesis of Yonsei University (2008)

Moon, Y.H.: A study on context prediction of student employment using decision tree algorithm. Master Thesis of Jeju University (2013)

Sang Ho, L.: Development of decision tree building and navigation component using C4.5 algorithm. Master Thesis of Ulsan University (2008)

Mamiulis, N., Cao, H. , Kollios, G., Hadjieleftheriou, M., Tao, Y., Cheung, D.W.: Mining, indexing, and querying historical spatiotemporal data. In: Proceedings of the 10th ACM SIGKDD International Conference Knowledge Discovery and Data Mining, pp.236–245 (2004)

Cao, H., Mamoulis, N., Cheung, D.W.: Mining frequent spatio-temporal sequential patterns. In: Proceedings Of the 5th IEEE International Conference on Data Mining, pp.82–89 (2005)

Nguyen, H.A., Giordano, S.: Context information prediction for social-based routing in opportunistic networks. J. Ad Hoc Netw. 10(8), 1557–1569 (2012)

Ji Wong, P.: An efficient algorithm for spatio-temporal moving pattern extraction. Master Thesis of Konkuk University (2006)

Quinlan, J.R.: C4.5: Programming for Machine Learning. Morgan Kaufmann, San Mateo (1993)

Mantas, C.J., Abellan, J.: Credal-C4.5: decision tree based on imprecise probabilities to classify noisy data. J. Expert Syst. Appl. 41(10), 4625–4637 (2014)