CFP -Workshop on Knowledge Graph Technology and Applications @ WWW2019


NOTICE: Due to many requests we received, we extend our deadline for 
paper submission to Feb 10, 2019.

Important Dates
Paper submission: Feb 10, 2019
Paper notification: Feb 25, 2019
Camera ready: Mar 1, 2019

The First International Workshop on Knowledge Graph Technology and 
Co-located with WWW2019 (
May 13, 2019, San Francisco, California, USA

Knowledge Graphs are graph structures that capture knowledge in the form 
of entities, relationships between them, properties, and additional 
information including provenance. Along with Semantic Web standards such 
as RDF, OWL, and SPARQL, advances in Machine Learning, Deep Learning, 
Natural Language Processing, and Information Retrieval has led to 
automated construction of knowledge graphs such as DBpedia, YAGO, 
Wikidata, proprietary Knowledge Graphs such as those from Google, 
LinkedIn, and Microsoft, and Product Knowledge Graphs from companies 
such as Amazon and eBay. Knowledge Graphs are used in a range of 
applications including search, question answering, data integration, 
recommender systems, etc., across several domains such as the Web, 
e-commerce, healthcare, geoscience, manufacturing, aviation, and power, 
oil and gas. There are several challenges related to knowledge graphs 
from the perspective of both the technology and its applications. This 
workshop aims to foster discussions along these perspectives.

Topics and Themes
Topics of interest include, but are not limited to the following. We 
especially encourage Knowledge Graph applications related to web search, 
conversational agents, recommender systems, search engines, and the ones 
in the Industrial domain such as manufacturing, aviation, power, oil and 

Construction and Maintenance of Knowledge Graphs
- Handling noisy and incomplete data
- Entity linking and resolution
- Consistency checking when adding new knowledge
- Collaborative maintenance of knowledge graphs
- Provenance solutions for Knowledge Graphs
- Handling uncertain content in Knowledge Graphs

Operations over Knowledge Graphs
- Innovative methods for querying and interacting with knowledge graphs
- Searching over knowledge graphs
- Reasoning over knowledge graphs
- Explaining knowledge graph contents

Mining Knowledge Graphs
- Machine Learning and deep learning techniques for knowledge graph mining
- Heterogeneous graph mining

Storage mechanisms for Knowledge Graphs
- Graph databases, triple stores
- New storage and indexing schemes for property graphs

Knowledge Graphs for NLP and IR
- Web search, conversational agents, recommender systems, information 
access systems, and summary generation

Knowledge Graphs in the industry
- manufacturing, aviation, power, oil and gas, healthcare, banking, 
finance, and IoT
- Industry use cases and best practices

Submission Guidelines
Authors can submit either full papers of 8 pages in length or short 
papers of 4 pages length in the ACM format 
(, with the 
"sigconf" option. Since we plan to follow single-blind review process, 
there is no need to anonymize the author list. Since the workshop papers 
will be included in the companion volume of The Web Conference 
proceedings, it is important to follow the suggested submission format. 
Submissions can be made using EasyChair at Authors of the 
accepted papers will be invited to give a short lightning talk and/or 
present a poster at the workshop.

High quality submissions with substantial revisions will be invited to 
submit to Data Intelligence Journal 
( and the Special Issue on 
Linked Data and Knowledge Graph in Large Organisations at the 
Information Journal 

Important Dates
Paper submission: Feb 10, 2019
Paper notification: Feb 25, 2019
Camera ready: Mar 1, 2019

Raghava Mutharaju:
Chenyan Xiong:
Ying Ding:

Workshop Organizers (in alphabetic order)
Huajun Chen,Zhejiang University, China
Laura Dietz, University of New Hampshire, USA
Ying Ding, Indiana University Bloomington, USA
Wendy Hall, University of Southampton, UK
James Hendler, Rensselaer Polytechnic Institute, USA
Deborah McGuinness, Rensselaer Polytechnic Institute, USA
Edgar Meij, Bloomberg LP, USA
Sam Molyneux, Chan Zuckerberg Initiative, USA
Varish Mulwad, GE Global Research Center, USA
Raghava Mutharaju, IIIT-Delhi, India
Jeff Z. Pan, University of Aberdeen, UK
Xiang Ren, University of Southern California, USA
Jie Tang, Tsinghua University, China
Alex Wade, Chan Zuckerberg Initiative, USA
Mengting Wan, University of California, San Diego (UCSD), USA
Chenyan Xiong, Carnegie Mellon University, USA
Min Zhang, Tsinghua University, China

Received on Thursday, 31 January 2019 00:33:07 UTC