M. Atzmueller, Subgroup Discovery. WIREs Data Mining and Knowledge Discovery, vol.5, pp.35-49, 2015.

M. Atzmueller and F. Lemmerich, Fast Subgroup Discovery for Continuous Target Concepts, Proc. International Symposium on Methodologies for Intelligent Systems, vol.5722, pp.1-15, 2009.

M. Atzmueller and T. Roth-berghofer, The Mining and Analysis Continuum of Explaining Uncovered, Proc. Research and Development in Intelligent Systems XXVII. SGAI 2010, pp.273-278, 2010.

O. Biran and C. Cotton, Explanation and Justification in Machine Learning: A Survey, IJCAI-17 Workshop on Explainable AI, 2017.

S. Bloemheuvel and B. Kloepper, Enhancing Sequential Pattern Mining Explainability with Markov Chain Probabilities, Proc. Dutch-Belgian Database Day, 2019.

W. Duivesteijn and J. Thaele, Understanding Where Your Classifier Does (Not) Work -The SCaPE Model Class for EMM, Proc. ICDM, pp.809-814, 2014.

S. Feng, X. Li, Y. Zeng, G. Cong, Y. Meng-chee et al., Personalized ranking metric embedding for next new poi recommendation, Proc. IJCAI, pp.2069-2075, 2015.

J. Fürnkranz, T. Kliegr, and H. Paulheim, On cognitive preferences and the plausibility of rule-based models, Mach. Learn, vol.109, issue.4, pp.853-898, 2020.

R. Guidotti, A. Monreale, F. Turini, D. Pedreschi, and F. Giannotti, A survey of methods for explaining black box models, 2018.

F. , M. Harper, and J. A. Konstan, The movielens datasets: History and context, ACM TiiS, vol.5, issue.4, 2015.

R. He, W. Kang, and J. Mcauley, Translation-based recommendation, Proc. RecSys, pp.161-169, 2017.

A. Henelius, K. Puolamäki, H. Boström, L. Asker, and P. Papapetrou, A peek into the black box: Exploring classifiers by randomization, Data Min. Knowl. Disc, vol.28, pp.1503-1529, 2014.

W. Kang and J. J. Mcauley, Self-attentive sequential recommendation, Proc. ICDM, pp.197-206, 2018.

F. Lemmerich, M. Atzmueller, and F. Puppe, Fast exhaustive subgroup discovery with numerical target concepts, Data Min. Knowl. Disc, vol.30, issue.3, pp.711-762, 2016.

X. Li and J. Huan, Constructivism Learning: A Learning Paradigm for Transparent Predictive Analytics, Proc. SIGKDD, pp.285-294, 2017.

C. Lonjarret, R. Auburtin, C. Robardet, and M. Plantevit, Sequential recommendation with metric models based on frequent sequences, 2020.

R. David and . Mandel, Counterfactual and Causal Explanation: From Early Theoretical Views To New Frontiers, The Psychology of Counterfactual Thinking, pp.23-39, 2007.

R. Mathonat, D. Nurbakova, J. Boulicaut, and M. Kaytoue, Seqscout: Using a bandit model to discover interesting subgroups in labeled sequences, Proc. DSAA, pp.81-90, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02282082

J. Mcauley, C. Targett, Q. Shi, A. Van-den, and . Hengel, Image-based recommendations on styles and substitutes, Proc. SIGIR, pp.43-52, 2015.

D. Mcsherry, Explanation in recommender systems, Artificial Intelligence Review, vol.24, issue.2, pp.179-197, 2005.

P. Pu and L. Chen, Trust building with explanation interfaces, Proc. IUI, pp.93-100, 2006.

S. Rendle, C. Freudenthaler, and L. Schmidt-thieme, Factorizing personalized markov chains for next-basket recommendation, Proc. WWW, pp.811-820, 2010.

S. Marco-túlio-ribeiro, C. Singh, and . Guestrin, why should I trust you?": Explaining the predictions of any classifier, Proc. KDD, pp.1135-1144, 2016.

S. Marco-tulio-ribeiro, C. Singh, and . Guestrin, Anchors: High-Precision Model-Agnostic Explanations, Proc. AAAI, 2018.

T. Roth-berghofer, S. Schulz, D. Leake, and D. Bahls, Explanation-aware computing, AI Magazine, vol.28, issue.4, 2007.

R. Thomas, J. Roth-berghofer, and . Cassens, Mapping Goals and Kinds of Explanations to the Knowledge Containers of Case-Based Reasoning Systems, Proc. ICCBR, number 3620 in LNAI, pp.451-464, 2005.

C. Roger and . Schank, Explanation Patterns: Understanding Mechanically and Creatively, 1986.

F. Sørmo, J. Cassens, and A. Aamodt, Explanation in casebased reasoning -perspectives and goals, Artificial Intelligence Review, vol.24, issue.2, pp.109-143, 2005.

N. Tintarev and J. Masthoff, Designing and evaluating explanations for recommender systems, Recommender systems handbook, pp.479-510, 2011.

G. Tolomei, F. Silvestri, A. Haines, and M. Lalmas, Interpretable predictions of tree-based ensembles via actionable feature tweaking, Proc. KDD, pp.465-474, 2017.

R. Michael, W. B. Wick, and . Thompson, Reconstructive expert system explanation, Artificial Intelligence, vol.54, issue.1-2, pp.33-70, 1992.

S. Wrobel, An algorithm for multi-relational discovery of subgroups, Proc. PKDD, number 1263 in LNCS, pp.78-87, 1997.