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MINDWALC: mining interpretable, discriminative walks for classification of nodes in a knowledge graph.

, , , и . BMC Medical Informatics Decis. Mak., 20-S (4): 191 (2020)

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Automated Extraction of Rules and Knowledge from Risk Analyses: a Ventilation Unit Demo., , , , , , , , и . ISWC (P&D/Industry/BlueSky), том 2180 из CEUR Workshop Proceedings, CEUR-WS.org, (2018)Walk Extraction Strategies for Node Embeddings with RDF2Vec in Knowledge Graphs., , , , , , , и . DEXA Workshops, том 1479 из Communications in Computer and Information Science, стр. 70-80. Springer, (2021)Self-Learning Algorithms for the Personalised Interaction with People with Dementia., , , , и . AAAI Workshops, том WS-18 из AAAI Technical Report, стр. 153-158. AAAI Press, (2018)Towards Adaptive Anomaly Detection and Root Cause Analysis by Automated Extraction of Knowledge from Risk Analyses., , , , , , , , и . SSN@ISWC, том 2213 из CEUR Workshop Proceedings, стр. 17-31. CEUR-WS.org, (2018)Inducing a Decision Tree with Discriminative Paths to Classify Entities in a Knowledge Graph., , , и . SEPDA@ISWC, том 2427 из CEUR Workshop Proceedings, стр. 1-6. CEUR-WS.org, (2019)Adaptive Anomaly Detection and Root Cause Analysis by Fusing Semantics and Machine Learning.. ESWC (Satellite Events), том 11155 из Lecture Notes in Computer Science, стр. 272-282. Springer, (2018)MAGIC: Mining an Augmented Graph using INK, starting from a CSV., , и . SemTab@ISWC, том 3103 из CEUR Workshop Proceedings, стр. 68-78. CEUR-WS.org, (2021)MINDWALC: mining interpretable, discriminative walks for classification of nodes in a knowledge graph., , , и . BMC Medical Informatics Decis. Mak., 20-S (4): 191 (2020)TALK: Tracking Activities by Linking Knowledge., , , , , и . Eng. Appl. Artif. Intell., (2023)Towards Knowledge-Driven Symptom Monitoring & Trigger Detection of Primary Headache Disorders., , , , , , , , , и . WWW (Companion Volume), стр. 264-268. ACM, (2022)