AAAI-MAKE 2019
AAAI 2019 Spring Symposium on Combining Machine Learning with Knowledge Engineering

Table of Contents

• Preface
  Andreas Martin, Knut Hinkelmann, Aurona Gerber, Doug Lenat, Frank van Harmelen and Peter Clark
  

Papers

• Knowledge Engineering and Machine Learning for Design and Use in Cyber-Physical Environments
  Michael Walch
• Leverage White-Collar Workers with AI
  Stephan Jüngling, Angelin Hofer
• SEVA: A Systems Engineer’s Virtual Assistant
  Jitin Krishnan, Patrick Coronado, Trevor Reed
• Virtual Bartender: A Dialog System Combining Data-Driven and Knowledge-Based Recommendation
  Knut Hinkelmann, Monika Blaser, Oliver Faust, Alexander Horst, Carlo Mehli
• Building Knowledge Base through Deep Learning Relation Extraction and Wikidata
  Pero Subasic, Hongfeng Yin, Xiao Lin
• Collaborative Learning of Concept Representations for Video Data
  Francisco Torres, Hoda Eldardiry, Gaurang Gavai, Chad Ramos
• Representation and Retrieval of Images by Means of Spatial Relations Between Objects
  Danilo Nunes, Leonardo Anjoletto Ferreira, Paulo E. Santos, Adam Pease
• Modularity as a Means for Complexity Management in Neural Networks Learning
  David Castillo-Bolado, Cayetano Guerra-Artal, Mario Hernandez-Tejera
• Applying the Concept of Knowledge Blockchains to Ontologies
  Hans-Georg Fill
• Combining Machine Learning with Knowledge Engineering to detect Fake News in Social Networks - A Survey
  Knut Hinkelmann, Sajjad Ahmed, Flavio Corradini
• Improving Topic Modeling for Textual Content with Knowledge Graph Embeddings
  Marco Brambilla, Birant Altinel
• The Lokahi Prototype: Toward the automatic Extraction of Entity Relationship Models from Text
  Michael Kaufmann
• DEXTER - Data EXTraction & Entity Recognition for Low Resource Datasets
  Nihal V. Nayak, Pratheek Mahishi, Sagar Rao
• CoKE : Word Sense Induction Using Contextualized Knowledge Embeddings
  Sanjana Ramprasad, James Maddox
• Learning Temporal Rules from Knowledge Graph Streams
  Pouya Ghiasnezhad Omran, Kewen Wang, Zhe Wang
• Duplicate Removal for Overlapping Clusters: A Study Using Social Media Data
  Amit Paul, Animesh Dutta
• Performance Measures Fusion for Experimental Comparison of Methods for Multi-label Classification
  Tome Eftimov, Dragi Kocev
• CrystalGAN: Learning to Discover Crystallographic Structures with Generative Adversarial Networks
  Asma Nouira, Nataliya Sokolovska, Jean-Claude Crivello
• Tree-based Regularization for Interpretable Readmission Prediction
  Jialiang Jiang, Sharon Hewner, Varun Chandola
• Towards an Assistive and Pattern Learning-driven Process Modeling Approach
  Emanuele Laurenzi, Knut Hinkelmann, Stephan Jüngling, Devid Montecchiari, Charuta Pande, Andreas Martin
• DeepLogic: Towards End-to-End Differentiable Logical Reasoning
  Nuri Cingillioglu, Alessandra Russo
• On the Capabilities of Logic Tensor Networks for Deductive Reasoning
  Federico Bianchi, Pascal Hitzler
• KINN: Incorporating Expert Knowledge in Neural Networks
  Muhammad Ali Chattha, Shoaib Ahmed Siddiqui, Muhammad Imran Malik, Ludger Van Elst, Andreas Dengel , Sheraz Ahmed,
• Learning and Engineering Similarity Functions for Business Recommenders and Clustering
  Hans Friedrich Witschel, Andreas Martin
• Leveraging Wikipedia for Ontology Pattern Population from Text
  Michelle Cheatham, James Lambert, Charles Vardeman II
• Metrics for Evaluating Quality of Embeddings for Ontological Concepts
  Faisal Alshargi, Saeedeh Shekarpour, Tommaso Soru, Amit Sheth
• Deconstructing the Final Frontier of Artificial Intelligence: Five Theses for a Constructivist Machine Learning (short paper)
  Thomas Schmid
• From Demonstrations and Knowledge Engineering to a DNN Agent in a Modern Open-World Video Game (short paper)
  Igor Borovikov, Ahmad Beirami

Poster & Extended Abstract

• PLOW: Probabilistic Logic Over the Well-Founded Semantics
  Benjamin Grosof, Theresa Swift
• Using Predicate Information from a Knowledge Graph to Identify Disease Trajectories
  Wytze Vlietstra, Rein Vos, Erik van Mulligen, Jan Kors
• A Proposal for Determining the Evidence Types of Biomedical Documents Using a Drug-drug Interaction Ontology and Machine Learning
  Linh Hoang, Richard D. Boyce, Mathias Brochhausen, Joseph Utecht, Jodi Schneider
• On Datasets for Evaluating Architectures for Learning to Reason
  Naveen Sundar Govindarajulu, Jean-Claude Paquin, Shreya Banerjee, Atriya Sen, Paul Mayol, Selmer Bringsjord