AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering

Keyphrases

Publications

2021

Monireh Ebrahimi, Md. Kamruzzaman Sarker, Federico Bianchi, Ning Xie, Aaron Eberhart, Derek Doran, HyeongSik Kim, Pascal Hitzler
Neuro-Symbolic Deductive Reasoning for Cross-Knowledge Graph Entailment. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
David Leake, Xiaomeng Ye, David J. Crandall
Supporting Case-Based Reasoning with Neural Networks: An Illustration for Case Adaptation. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Sutapa Mondal, Sumit Bhatia, Raghava Mutharaju
EmEL++: Embeddings for EL++ Description Logic. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Deepak Nagaraj, Rhett Dobinson, Dirk Werth
Towards Kinematically Constrained Real Time Human Pose Estimation using Sparse IMUs. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Ole-Edvard Ørebæk, Marius Geitle
Exploring the Hyperparameters of XGBoost Through 3D Visualizations. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Achim Reiz, Mohamad Albadawi, Kurt Sandkuhl, Matthias Vahl, Dennis Sidin
Towards More Robust Fashion Recognition by Combining of Deep-Learning-Based Detection with Semantic Reasoning. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Mahin Ramezani, Guru Ilangovan, Hye-Chung Kum
Evaluation of Machine Learning Algorithms in a Human-Computer Hybrid Record Linkage System. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Gertjan J. Burghouts, Fieke Hillerström
ZERO - Detect objects without training examples by knowing their parts. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Shaban Shabani, Zarina Charlesworth, Maria Sokhn, Heiko Schuldt
SAMS: Human-in-the-loop Approach to Combat the Sharing of Digital Misinformation. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Agnese Chiatti, Enrico Motta, Enrico Daga, Gianluca Bardaro
Fit to Measure: Reasoning About Sizes for Robust Object Recognition. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Johannes Sahlin, Håkan Sundell, Håkan Alm, Jesper Holgersson
Evaluating Artificial Short Message Service Campaigns Through Rule Based Multi-instance Multi-label Classification. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Kaushik Roy, Qi Zhang, Manas Gaur, Amit P. Sheth
Knowledge Infused Policy Gradients for Adaptive Pandemic Control. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Hossein Rahnama, Marjan Alirezaie, Alex Pentland
A Neural-Symbolic Approach for User Mental Modeling: A Step Towards Building Exchangeable Identities. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Jip J. van Stijn, Mark A. Neerincx, Annette ten Teije, Steven Vethman
Team Design Patterns for Moral Decisions in Hybrid Intelligent Systems: A Case Study of Bias Mitigation. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Carlo Mehli, Knut Hinkelmann, Stephan Jüngling
Decision Support combining Machine Learning, Knowledge Representation and Case-Based Reasoning. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Arzam Kotriwala, Benjamin Klöpper, Marcel Dix, Gayathri Gopalakrishnan, Dawid Ziobro, Andreas Potschka
XAI for Operations in the Process Industry - Applications, Theses, and Research Directions. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Kaushik Roy, Usha Lokala, Vedant Khandelwal, Amit P. Sheth
"Is depression related to cannabis?": A knowledge-infused model for Entity and Relation Extraction with Limited Supervision. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Raymond J. Mooney, Jude W. Shavlik
A Recap of Early Work on Theory and Knowledge Refinement. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Benedikt Wagner, Artur d'Avila Garcez
Neural-Symbolic Integration for Fairness in AI. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Edmund Dervakos, Giorgos Filandrianos, Konstantinos Thomas, Alexios Mandalios, Chrysoula Zerva, Giorgos Stamou
Semantic Enrichment of Pretrained Embedding Output for Unsupervised IR. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Meghamala Sinha, Stephen A. Ramsey
Using a General Prior Knowledge Graph to Improve Data-Driven Causal Network Learning. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
William Broniec, Sungeun An, Spencer Rugaber, Ashok K. Goel
Guiding Parameter Estimation of Agent-Based Modeling Through Knowledge-Based Function Approximation. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Sophie Neutel, Maaike H. T. de Boer
Towards Automatic Ontology Alignment using BERT. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Miriam Herold, Mirjam Minor
Ontology-based Transfer Learning in the Airport and Warehouse Logistics Domains. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Dorothea Tsatsou, Konstantinos Karageorgos, Anastasios Dimou, Javier Carbó, José M. Molina López, Petros Daras
Towards Unsupervised Knowledge Extraction. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Joachim de Greeff, Maaike H. T. de Boer, Fieke H. J. Hillerström, Freek Bomhof, Wiard Jorritsma, Mark A. Neerincx
The FATE System: FAir, Transparent and Explainable Decision Making. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Guusje Boomgaard, Selene Baez Santamaría, Ilaria Tiddi, Robert-Jan Sips, Zoltán Szlávik
Learning Profile-Based Recommendations for Medical Search Auto-Complete. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
David Morandi, Stephan Jüngling
Anomaly Detection in Railway Infrastructure. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Jan Meiswinkel, Patrick Levi, Rainer Hoch
The Significance of Computational Performance for Enterprise AI in Question-Answering. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Maaike H. T. de Boer, Fieke Hillerström
Hybrid AI using Graph Neural Networks in Scene Classification. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Sheikh Rabiul Islam, William Eberle
Implications of Combining Domain Knowledge in Explainable Artificial Intelligence. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Philipp Behnen, Felix Kruse, Jorge Marx Gómez
Enhancement of Record Linkage by Using Attributes containing Natural Language Text. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Charuta Pande, Hans Friedrich Witschel, Andreas Martin, Devid Montecchiari
Hybrid Conversational AI for Intelligent Tutoring Systems. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Andreas Martin, Knut Hinkelmann
AAAI-MAKE 2021: Combining Machine Learning and Knowledge Engineering. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
René Keßler, Christian Melching, Ralph Goehrs, Jorge Marx Gómez
Using Camera-Drones and Artificial Intelligence to Automate Warehouse Inventory. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Sunday C. Ngwobia, Saeedeh Shekarpour, Faisal Alshargi
Capturing Knowledge of Emerging Entities from Extended Search Snippets. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Margaret Warren, David A. Shamma, Patrick J. Hayes
Knowledge Engineering with Image Data in Real-World Settings. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Arturo Castellanos, Alfred Castillo, Monica Chiarini Tremblay, Roman Lukyanenko, Jeffrey Parsons, Veda C. Storey
Improving Machine Learning Performance Using Conceptual Modeling. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Amit Bhatia, Alessandro Pinto
Automated Construction of Knowledge-Bases for Safety Critical Applications: Challenges and Opportunities. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Mohita Chaudhary, Mohamed Sadok Gastli, Lobna Nassar, Fakhri Karray
Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)
Thomas Schmid
Batch-like Online Learning for More Robust Hybrid Artificial Intelligence: Deconstruction as a Machine Learning Process. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (2021)

volume 2846, 2021

Proceedings of the AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021), Stanford University, Palo Alto, California, USA, March 22-24, 2021. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering 2846 (2021)

2019

volume 2350, 2019

Proceedings of the AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering (AAAI-MAKE 2019) Stanford University, Palo Alto, California, USA, March 25-27, 2019., Stanford University, Palo Alto, California, USA, March 25-27, 2019. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering 2350 (2019)