HINMINE: heterogeneous information network mining with information retrieval heuristics

Author:

Kralj JanORCID,Robnik-Šikonja Marko,Lavrač Nada

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,Hardware and Architecture,Information Systems,Software

Reference34 articles.

1. Belkin, M., Niyogi, P., & Sindhwani, V. (2006). Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. Journal of machine learning research, 7, 2399–2434.

2. Burt, R., & Minor, M. (1983). Applied Network Analysis: A Methodological Introduction: Sage Publications.

3. Cantador, I., Brusilovsky, P., & Kuflik, T. (2011). 2Nd workshop on information heterogeneity and fusion in recommender systems (hetrec 2011). In Proceedings of the 5th ACM conference on Recommender systems. RecSys. New York: ACM.

4. Consortium (2000). Gene ontology: tool for the unification of biology. The gene ontology consortium. Nature genetics, 25(1), 25–29.

5. de Sousa, C. A. R., Rezende, S. O., & Batista, G. E (2013). Influence of graph construction on semi-supervised learning. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 160–175): Springer.

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