2019 WWW Workshop | Knowledge Graph Technology and Applications

2019 年 2 月 3 日 开放知识图谱


               

2019 WWW WORKSHOP ON

Knowledge Graph Technology and Applications

May 13-17, 2019/ San Francisco

                 

INTRODUCTION

Knowledge Graphs are graph structures that capture knowledge in the form of entities and the relationships between them, and optionally the provenance information. 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, Google’s and LinkedIn’s  Knowledge Graph, Microsoft’s Satori, and Product Knowledge Graph from Amazon and eBay. Knowledge Graphs are used in several applications such as search, question answering, data integration, recommendation systems etc., across several domains such as healthcare, geosciences, manufacturing, aviation, 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, recommendation systems, and in the Industrial domain such as manufacturing, aviation, power, oil and gas.

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 industrial domain

  • manufacturing, aviation, power, oil and gas, healthcare, banking, finance, and IoT

Industry use cases and best practices

  • manufacturing, aviation, power, oil and gas, healthcare, banking, finance, and IoT

  • Industry use cases and best practices


SPEAKERS

TO BE ANNOUNCED...


SUBMISSION GUIDELINES

Authors can submit either full papers of 8 pages in length or short papers of 4 pages length in the ACM format (https://www.acm.org/publications/proceedings-template), 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 (https://easychair.org/conferences/?conf=kgtawww19). Authors of the accepted papers will be invited to give a short lightning talk of 5 minutes and/or present a poster at the workshop.
 High quality submissions with substantial revisions will be invited to submit to Data Intelligence Journal (http://www.data-intelligence-journal.org/) and the Special Issue on “Linked Data and Knowledge Graph in Large Organisations” at the Information Journal (https://www.mdpi.com/journal/information/special_issues/Knowledge_Graphs).


Program Committee (TO Be Confirmed)

           

   More members will be added as required

                       

  • Mark Musen, Stanford, USA

  • Stefan Decker, Fraunhofer FIT, Germany

  • Jie Tang, Tsinghua University, China

  • Paul Groth, Elsevier, the Netherlands

  • Barend Mons, Leiden University, the Netherlands

  • Yizhou Sun, UCLA, USA

  • Michel Dumontier, Universiteit Maastricht, the Netherlands

  • Natasha Noy, Google, USA

  • Ramanathan V. Guha, Google

  • Andrew Moore, CMU, USA

  • Soren Auer, Leibniz University of Hannover, Germany

  • Juan Sequeda, Capsenta, USA

  • Freddy Lecue, Accenture Technology Labs, Ireland

  • Steve Gustafson, Maana, USA

  • Craig Knoblock, University of Southern California, USA

  • Pascal Hitzler, Wright State University, USA

  • Tim Finin, University of Maryland, Baltimore County, USA

  • Axel Polleres, WU Vienna, Austria

  • Amelie Gyrard, Wright State University, USA

  • Pankesh Patel, Fraunhofer, USA

  • Peter Haase, metaphacts GmbH, Germany

  • Muhammad Intizar Ali, Insight Center, Ireland

  • Krzysztof Janowicz, UCSB, USA

  • Paul Groth, Elsevier Labs, Netherlands


ABOUT US

The workshop participants will be open for the whole conference. Each submitted paper will be evaluated by three reviewers from the aspects of novelty, significance, technique sound, experiments, and presentations. The reviewers will be program committee members or researchers recommended by the members.


IMPORTANT DATES

    Paper submissions: Feb 10, 2019

    Author notifications: Feb 25, 2019

    Camera-Ready version: Mar 1, 2019



OpenKG.CN


中文开放知识图谱(简称OpenKG.CN)旨在促进中文知识图谱数据的开放与互联,促进知识图谱和语义技术的普及和广泛应用。

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