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Mining Subjectively Interesting Attributed Subgraphs., , , , , and . CoRR, (2019)SIAS-miner: mining subjectively interesting attributed subgraphs., , , , , and . Data Min. Knowl. Discov., 34 (2): 355-393 (2020)DeepLSH: Deep Locality-Sensitive Hash Learning for Fast and Efficient Near-Duplicate Crash Report Detection., , , , and . CoRR, (2023)On-Premise AIOps Infrastructure for a Software Editor SME: An Experience Report., , , and . ESEC/SIGSOFT FSE, page 1820-1831. ACM, (2023)Découverte de sous-groupes de prédictions interprétables pour le triage d'incidents., , , , and . EGC, volume E-38 of RNTI, page 411-418. Editions RNTI, (2022)Mining Java Memory Errors using Subjective Interesting Subgroups with Hierarchical Targets., , , , , and . ICDM (Workshops), page 1221-1230. IEEE, (2023)Interpretable Summaries of Black Box Incident Triaging with Subgroup Discovery., , , , and . DSAA, page 1-10. IEEE, (2021)User-Driven Geolocated Event Detection in Social Media., , , and . IEEE Trans. Knowl. Data Eng., 33 (2): 796-809 (2021)Gibbs Sampling Subjectively Interesting Tiles., , , , and . IDA, volume 12080 of Lecture Notes in Computer Science, page 80-92. Springer, (2020)FSSD - A Fast and Efficient Algorithm for Subgroup Set Discovery., , , , , , and . DSAA, page 91-99. IEEE, (2019)