SEPDA 2019
The 4th International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019)

Table of Contents

Session 1: Knowledge Graph and Knowledge Base

• Inducing a Decision Tree with Discriminative Paths to Classify Entities in a Knowledge Graph 1-6
  Gilles Vandewiele, Bram Steenwinckel, Femke Ongenae, Filip De Turck
• Aero: An Evidence-based Semantic Web Knowledge Base of Cancer Behavioral Risk Factors 7-11
  Hansi Zhang, Xing He, Tyler Harrison, Jiang Bian
• Generating Knowledge Graphs from Scientific Literature of Degenerative Diseases 12-23
  Anderson Rossanez, Julio Cesar dos Reis

Session 2: Ontology-Based Tools and Analytics

• An Ontology-Powered Dialogue Engine For Patient Communication of Vaccines 24-30
  Muhammad Amith, Rebecca Lin, Licong Cui, Dennis Wang, Anna Zhu, Grace Xiong, Hua Xu, Kirk Roberts, Cui Tao
• A Multi-Source Linked Open Data Fusion Method for Gene Disorder Drug Relationship Querying 31-35
  Guozheng Rao, Li Zhang, Xiaowang Zhang, Wenwen Li, Fang Li, Cui Tao
• Taxonomy Embeddings on PubMed Article Subject Headings 36-47
  Alyssa Lees, Jacek Korycki, Chris Welty, Shubin Zhao

Session 3: Machine Learning Applications

• Using Deep Neural Network to Identify Cancer Survivors Living with Post-Traumatic Stress Disorder on Social Media 48-52
  Nur Hafieza Ismail, Ninghao Liu, Mengnan Du, Zhe He, Xia Hu
• Treatment Effect Prediction with Generative Adversarial Networks Using Electronic Health Records 53-57
  Jiebin Chu, Wei Dong, Zhengxing Huang
• Feature Compression for Predicting Effective Drug Combination 58-62
  Guocai Chen, Xiaoqian Jiang, Wenjin Zheng

Session 4: Ontology Development and Text Mining

• Ontology for Documentation of Variable and Data Source Selection Process to Support Integrative Data Analysis in Cancer Outcomes Research 63-67
  Hansi Zhang, Yi Guo, Jiang Bian
• Semantic Similarity of Side Effect and Indication Relations of Drugs Inferred from Neural Embedding 68-77
  Keyuan Jiang, Tingyu Chen, Liyuan Huang, Gelareh Karbaschi, Gordon Bernard