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ORCIDAAAI Spring Symposium 2019 - Combining Machine Learning with Knowledge Engineering: Palo Alto, CA, USA
- Andreas Martin, Knut Hinkelmann, Aurona Gerber, Doug Lenat, Frank van Harmelen, Peter Clark:
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. CEUR Workshop Proceedings 2350, CEUR-WS.org 2019 - Michael Walch:
Knowledge Engineering and Machine Learning for Design and Use in Cyber-Physical Environments. - Stephan Jüngling, Angelin Hofer:
Leverage White-Collar Workers with AI. - Jitin Krishnan, Patrick Coronado, Trevor Reed:
SEVA: A Systems Engineer's Virtual Assistant. - Knut Hinkelmann, Monika Blaser, Oliver Faust, Alexander Horst, Carlo Mehli:
Virtual Bartender: A Dialog System Combining Data-Driven and Knowledge-Based Recommendation. - Pero Subasic, Hongfeng Yin, Xiao Lin:
Building Knowledge Base through Deep Learning Relation Extraction and Wikidata. - Francisco Torres, Hoda Eldardiry, Gaurang Gavai, Chad Ramos:
Collaborative Learning of Concept Representations for Video Data. - Danilo Nunes, Leonardo Anjoletto Ferreira, Paulo E. Santos, Adam Pease:
Representation and Retrieval of Images by Means of Spatial Relations Between Objects. - David Castillo-Bolado, Cayetano Guerra-Artal, Mario Hernández-Tejera:
Modularity as a Means for Complexity Management in Neural Networks Learning. - Hans-Georg Fill:
Applying the Concept of Knowledge Blockchains to Ontologies. - Knut Hinkelmann, Sajjad Ahmed, Flavio Corradini:
Combining Machine Learning with Knowledge Engineering to detect Fake News in Social Networks - A Survey. - Marco Brambilla, Birant Altinel:
Improving Topic Modeling for Textual Content with Knowledge Graph Embeddings. - Michael Kaufmann:
The Lokahi Prototype: Toward the automatic Extraction of Entity Relationship Models from Text. - Nihal V. Nayak, Pratheek Mahishi, Sagar Rao:
DEXTER - Data EXTraction & Entity Recognition for Low Resource Datasets. - Sanjana Ramprasad, James Maddox:
CoKE : Word Sense Induction Using Contextualized Knowledge Embeddings. - Pouya Ghiasnezhad Omran
, Kewen Wang, Zhe Wang:
Learning Temporal Rules from Knowledge Graph Streams. - Amit Paul, Animesh Dutta:
Duplicate Removal for Overlapping Clusters: A Study Using Social Media Data. - Tome Eftimov, Dragi Kocev:
Performance Measures Fusion for Experimental Comparison of Methods for Multi-label Classification. - Asma Nouira, Nataliya Sokolovska, Jean-Claude Crivello:
CrystalGAN: Learning to Discover Crystallographic Structures with Generative Adversarial Networks. - Jialiang Jiang, Sharon Hewner, Varun Chandola:
Tree-based Regularization for Interpretable Readmission Prediction. - Emanuele Laurenzi, Knut Hinkelmann, Stephan Jüngling, Devid Montecchiari, Charuta Pande, Andreas Martin:
Towards an Assistive and Pattern Learning-driven Process Modeling Approach. - Nuri Cingillioglu, Alessandra Russo:
DeepLogic: Towards End-to-End Differentiable Logical Reasoning. - Federico Bianchi, Pascal Hitzler:
On the Capabilities of Logic Tensor Networks for Deductive Reasoning. - Muhammad Ali Chattha, Shoaib Ahmed Siddiqui, Muhammad Imran Malik, Ludger van Elst, Andreas Dengel, Sheraz Ahmed:
KINN: Incorporating Expert Knowledge in Neural Networks. - Hans Friedrich Witschel, Andreas Martin:
Learning and Engineering Similarity Functions for Business Recommenders and Clustering. - Michelle Cheatham, James Lambert, Charles F. Vardeman II:
Leveraging Wikipedia for Ontology Pattern Population from Text. - Faisal Alshargi, Saeedeh Shekarpour, Tommaso Soru, Amit P. Sheth:
Metrics for Evaluating Quality of Embeddings for Ontological Concepts. - Thomas Schmid:
Deconstructing the Final Frontier of Artificial Intelligence: Five Theses for a Constructivist Machine Learning. - Igor Borovikov, Ahmad Beirami:
From Demonstrations and Knowledge Engineering to a DNN Agent in a Modern Open-World Video Game.
Poster & Extended Abstract
- Benjamin N. Grosof, Theresa Swift:
PLOW: Probabilistic Logic Over the Well-Founded Semantics. - Wytze Vlietstra, Rein Vos, Erik M. van Mulligen, Jan A. Kors:
Using Predicate Information from a Knowledge Graph to Identify Disease Trajectories. - Linh Hoang, Richard D. Boyce, Mathias Brochhausen, Joseph Utecht, Jodi Schneider:
A Proposal for Determining the Evidence Types of Biomedical Documents Using a Drug-drug Interaction Ontology and Machine Learning. - Naveen Sundar Govindarajulu, Jean-Claude Paquin, Shreya Banerjee, Atriya Sen, Paul Mayol, Selmer Bringsjord:
On Datasets for Evaluating Architectures for Learning to Reason.
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