Second Workshop on Knowledge Graphs and Big Data

***Online Workshop***

In Conjunction with IEEE Big Data 2022

SCOPE and OBJECTIVES


Knowledge graphs represent world knowledge in entities linked through relationships enabling effective navigation and pattern discovery. Many enterprises have built large-scale knowledge graphs that drive their products. Moreover, simulations and advanced experiments in scientific research have also generated unprecedented big data. Data-driven machine learning methods have shown great potential to accelerate scientific discovery. However, significant amounts of the big data remain underutilized due to data isolation, distribution, and heterogeneity. Applying knowledge graph techniques for extraction, integration, and discovery in big scientific and experimental data is a promising direction.

This workshop provides a platform for knowledge graph researchers and practitioner in both business and scientific domains to exchange research ideas and solutions related to knowledge graph representation, miming, reasoning, and applications in big data settings.


Call for Papers


The following is a list of topics (but not limited) related this workshop:

  • Knowledge graphs for big scientific and experimental data
  • Big knowledge graph representation and modeling
  • Constructing knowledge graphs from structured and unstructured data
  • Big knowledge graph embeddings
  • Link prediction
  • Knowledge graph completion
  • Natural language processing and knowledge graph
  • Semantic Web, ontology and knowledge graph
  • Knowledge graph for recommender systems
  • Scalable knowledge graph reasoning and inference
  • Knowledge graph for big data processing
  • Knowledge graph applications in business, biomedical, healthcare, etc.
  • Knowledge graph visualization and human interaction
  • Knowledge graph for explainable AI
  • Knowledge graph alignment
  • Graph neural networks and big knowledge graphs
  • Scalable knowledge graph storage and query processing
  • Record linkage using knowledge graphs

Important Dates


  • Nov. 1, 2022: Due date for full workshop papers submission
  • Nov. 20, 2022: Notification of paper acceptance to authors
  • Nov. 27, 2022: Camera-ready of accepted papers
  • Dec. 17, 2022: Online Workshop


Paper Submission


submission link: Click Here or you can find the workshop submission link from the list of workshops Here.

Note:

  1. This workshop accepts both long papers (up to 10 pages) and short/position papers (2-4 pages).
  2. Papers should be formatted to IEEE Computer Society Proceedings Manuscript.
  3. Formatting Guidelines ( https://www.ieee.org/conferences/publishing/templates.html ).
  4. Papers should be in the IEEE 2-column format.
  5. Full registration of IEEE BigData 2022 is required for at least one of the authors for participating in the workshop.

Workshop Organizers


  • Yuan An, Drexel University, ya45@drexel.edu
  • Jane Greenberg, Drexel University, jg3243@drexel.edu
  • Yuan Ling, Amazon.com, ericalingyuan@gmail.com
  • Alex Kalinowski, Drexel University, ajk437@drexel.edu


Program Committee


  • Corey Harper, Elsevier Labs, USA
  • Diego Gomez-Gualdron, Colorado School of Mines, USA
  • Edson Lucas, IPRJ/UERJ Polytechnic Institute, Brazil
  • Fernando Uribe-Romo, University of Central Florida, USA
  • Paulo Alencar, University of Waterloo, Canada
  • Ritu Khare, IQIVIA, USA
  • Ron Daniel, Elsevier Labs, USA
  • Sadid Hasan, CVS Health, USA
  • Sana Imtiaz, Kry International AB, Sweden
  • Scott McClellan, Drexel University, USA
  • Xintong Zhao, Drexel University, USA
  • Zachary Trautt, National Institute of Standards and Technology (NIST), USA
  • Zainab Abbas, KTH Royal Institute of Technology, Sweden

Accepted Papers


  • Runyu Ni, Hiroki Shibata, and Yasufumi Takama. Learning Framework of Entity and Entity Type Composition Representation for Knowledge Graph Completion
  • Kara Schatz, Daniel Korn, Alexander Tropsha, and Rada Chirkova. Workflow for Domain- and Task-Sensitive Curation of Knowledge Graphs, with Use Case of DRKG
  • Miyu Fujii, David Taingngin, Keiichiro Yamamura, Nozomi Hata, Hiroki Kai, Ryuji Noda, Hiroki Ishikura, Tatsuru Higurashi, and Katsuki Fujisawa. Development and Evaluation of Embedding Methods for Graphs with Multi Attributes
  • Ted Holmberg, Elias Ioup, and Mahdi Abdelguerfi. A Stochastic Geo-spatiotemporal Bipartite Network to Optimize GCOOS Sensor Placement Strategies
  • Min Zhang, Song Peng, Hao Yang, Yanqing Zhao, XiaoSong Qiao, Junhao Zhu, Shimin Tao, Ying Qin, and Yanfei Jiang. EntityRank: Unsupervised Mining of Bilingual Named Entity Pairs from Parallel Corpora for Neural Machine Translation
  • Phuc Nguyen and Hideaki Takeda. Wikidata-lite for Knowledge Extraction and Exploration
  • Yuan An, Jane Greenberg, Xiaohua Hu, Alex Kalinowski, Xiao Fang, Xintong Zhao, Scott McClellan, Fernando J. Uribe-Romo, Diego A. Gómez-Gualdrón, Kyle Langlois, Jacob Furst, Fernando Fajardo-Rojas, Katherine Ardila, Semion K. Saikin, Corey A. Harper Harper, and Ron Daniel. Exploring Pre-Trained Language Models to Build Knowledge Graph for Metal-Organic Frameworks (MOFs)
  • Sukhwan Jung and Aviv Segev. Optimizing the Descendant-Aware Clustering Parameters
  • Li Yuanzhuo. Ripl: Document-Level Event Argument Extraction via Role-aware Interactive Pointer Labeling Network


Agenda


2nd Workshop on Knowledge Graphs and Big Data

In Conjunction with IEEE Big Data 2022

Saturday, Dec. 17, 2022

Workshop Co-Chairs: Yuan An, Jane Greenberg, Yuan Ling, Alex Kalinowski

Time (Japan Standard Time)

Title

Presenter/Author

9:00-9:05am

Welcome

Yuan An

9:05-9:25am

Learning Framework of Entity and Entity Type Composition Representation for Knowledge Graph Completion

Runyu Ni, Hiroki Shibata, and Yasufumi Takama

9:25-9:45am

Workflow for Domain- and Task-Sensitive Curation of Knowledge Graphs, with Use Case of DRKG

Kara Schatz, Daniel Korn, Alexander Tropsha, and Rada Chirkova

9:45-10:05am

Development and Evaluation of Embedding Methods for Graphs with Multi Attributes

Miyu Fujii, David Taingngin, Keiichiro Yamamura, Nozomi Hata, Hiroki Kai, Ryuji Noda, Hiroki Ishikura, Tatsuru Higurashi, and Katsuki Fujisawa

10:05-10:25am

A Stochastic Geo-spatiotemporal Bipartite Network to Optimize GCOOS Sensor Placement Strategies

Ted Holmberg, Elias Ioup, and Mahdi Abdelguerfi

10:25-10:45am

EntityRank: Unsupervised Mining of Bilingual Named Entity Pairs from Parallel Corpora for Neural Machine Translation

Min Zhang, Song Peng, Hao Yang, Yanqing Zhao, XiaoSong Qiao, Junhao Zhu, Shimin Tao, Ying Qin, and Yanfei Jiang

10:45-10:55am

Coffee Break

10:55-11:15am

Wikidata-lite for Knowledge Extraction and Exploration

Phuc Nguyen and Hideaki Takeda

11:15-11:35am

Exploring Pre-Trained Language Models to Build Knowledge Graph for Metal-Organic Frameworks (MOFs)

Alex Kalinowski

11:35-11:55am

Optimizing the Descendant-Aware Clustering Parameters

Sukhwan Jung and Aviv Segev

11:55-12:15pm

Ripl: Document-Level Event Argument Extraction via Role-aware Interactive Pointer Labeling Network

Li Yuanzhuo

12:15-12:30pm

Closing Remarks and Future Suggestions