1. Alam, M., Coulet, A., Napoli, A., & Smail-Tabbone, M. (2012). Formal concept analysis applied to transcriptomic data. In Proceedings of The Ninth International Conference on Concept Lattices and Their Applications (CLA 2012), Fuengirola, Spain.
2. Andrews, A., & Orphanides, C. (2010). Analysis of large data sets using formal concept lattices. In Kryszkiewicz, M., & Obiedkov, S. (Eds.), Proceedings of the 7th International Conference on Concept Lattices and Their Applications (CLA 2010), Seville, Spain: University of Seville (pp. 104-115). ISBN 978-84614-4027-6.
3. Andrews, S. (2011). In-Close2, a high performance formal concept miner. In Andrews, S., Polovina, S., Hill, R., Akhgar, B. (Eds.), Proceedings of the ICCS-ConceptStruct 2011 (LNCS, vol. 6828, pp. 50–62). Heidelberg, Germany: Springer.
4. Andrews, S., Orphanides, C., & Polovina, S. (2011). Visualising computational intelligence through converting data into formal concepts. Next generation data technologies for collective computational intelligence (pp. 139-165).
5. Belohlavek, R., Grissa, D., Guillaume, S., Mephu Nguifo, E., & Outrata, J. (2011, October 17-20). Boolean factors as a means of clustering of interestingness measures of association rules. In Proceedings of The Eighth International Conference on Concept Lattices and Their Applications, Nancy, France.