[CFP] TEXT2KG@ The ESWC Conference 2024 – Third International Workshop on Knowledge Graph Generation from Text

[First Call for Papers]
TEXT2KG-2024: Third International Workshop on Knowledge Graph Generation
from Text collocated with ESWC-2024
Date: May 26 - May 30, 2024
in Hersonissos, Greece
https://aiisc.ai/text2kg2024/


*INTERNATIONAL WORKSHOP ON KNOWLEDGE GRAPH GENERATION FROM TEXT (TEXT2KG
2024)*

This workshop aims to bring together researchers from multiple focus areas
such as Natural Language Processing (NLP), Entity Linking (EL), Relation
Extraction (RE), Knowledge Representation and Reasoning (KRR), Deep
Learning (DL), Knowledge Base Construction (KBC), Large Language Models
(LLMs), Semantic Web, Linked Data, and other related fields to foster a
discussion and enhance the state-of-the-art in knowledge graph generation
from text.
The participants will find opportunities to present and hear about other
emerging research and applications, to exchange ideas and experiences, and
to identify new opportunities for collaborations across disciplines. We
plan to involve the many prominent research groups in the Semantic Web
community which in the last years focused on the generation of knowledge
graphs from textual sources in different fields, such as research data
(ORKG, AI-KG, Nano publications), question answering (ParaQA, NSQA), common
sense (CSKG), automotive (CoSI, ASKG), biomedical (Hetionet), and many
others.

*THEMES & TOPICS *

We are interested in (including but not limited to) the following themes
and topics that study the generation of Knowledge Graphs from text, based
on quantitative, qualitative, and mixed research methods.


   - Approaches for generating Knowledge Graphs from text
   - Ontologies for representing provenance/metadata of generated Knowledge
   Graphs
   - Benchmarks for KG generation from text
   - Evaluation methods for KGs generated from text
   - Industrial applications involving KGs generation from text
   - Entity and relation extraction
   - Entity and relation linking
   - Semantic Parsing
   - Open Information Extraction
   - Deep Learning and Generative approaches
   - Human-in-the-loop methods
   - Large Language Models and Knowledge Graphs

Paper submissions due: March 7, 2024

Final decision notification: April 4, 2024

Camera-ready submissions due: April 18th, 2024

*Submission Instructions*

We invite full research papers, negative results, position papers, dataset
and system demo papers. Submissions must be original and should not have
been published previously or be under consideration for publication while
being evaluated for this workshop. Submissions will be evaluated by the
program committee based on the quality of the work and its fit to the
workshop themes. All submissions are double-blind and a high-resolution PDF
of the paper should be uploaded to the EasyChair submission site before the
paper submission deadline. The accepted papers will be presented at the
Text2KG workshop integrated with the conference, and they will be published
as CEUR proceedings. All must be submitted and formatted in the style of
the CEUR proceedings format. For details on CEUR style, see CEUR’s Author
Instruction. Overleaf Template:
https://www.overleaf.com/latex/templates/template-for-submissions-to-ceur-workshop-proceedings-ceur-ws-dot-org/wqyfdgftmcfw

*Submission Link:* https://easychair.org/conferences/?conf=text2kg2024

*Workshop Link: *https://aiisc.ai/text2kg2024/

*Contact Person: *Sanju Tiwari <tiwarisanju18@ieee.org> (Please feel free
to write…)



*Organizing Chairs:*

Sanju Tiwari, BVICAM, New Delhi, India & UAT Mexico

Nandana Mihindukulasooriya, MIT-IBM Watson AI Lab, USA

Francesco Osborne, KMi, The Open University

Dimitris Kontokostas, Diffbot, Greece
Jennifer D’Souza, TIB, Germany

Mayank Kejriwal, University of Southern California, USA



*Publicity Chair:*

Joey Yip, University of South Carolina, USA



*Advisory Committee *

· Edlira Vakaj, Birmigham City University, UK

· Anna Fensel, Wageningen University & Research, Austria

· Maria Esther Vidal, Leibniz University of Hannover and TIB, Germany

· Amit Sheth, University of South Carolina, USA

· Sören Auer, Leibniz University of Hannover and TIB, Germany

· Enrico Motta, The Open University, United Kingdom

· Fernando Ortiz-Rodriguez, Universidad Autonoma de Tamaulipas, Mexico

· Sven Groppe, University of Lubeck, Germany

========================================================================
TEXT2KG Collocated Event: First International Health Intelligence Challenge

Health-related data, encompassing biomedical, behavioural, and
socio-demographic information along with various contextual information, is
distributed across multiple information systems and datasets. These systems
employ diverse technologies and data structures, including natural
language, complicating the task of making data findable, accessible,
interoperable, and reusable. The use of varied terminologies to annotate
and describe this data adds to the complexity. Our challenge is to
integrate and make this data available as actionable intelligence for
health decision-makers, aiding in effective individual and population
disease prevention and control. This integration aims to save lives and
livelihoods and reduce the impact on economies and societies.

*Weblink: *
https://healthintelligencepartnershipproject.github.io/challenges/hintchallenge/index.html
Awards

The first, second, and third best health intelligence solution are going to
be awarded as follows:
*First Place:* TBA
*Second Place:* TBA
*Third Place:* TBA

*Organizer: *Dusan MILOVANOVIC, WHO, Geneva, Switzerland


Please feel free to ask if you have any queries.


-- 
Regards
Dr. Sanju Tiwari (CEO & Founder of Shodhguru Research Labs)
Full Professor, BVICAM, New Delhi, India
Sr. Researcher, Universidad Autonoma de Tamaulipas, Mexico
Resarch Fellow of ORKG, TIB Hannover, Germany
Visiting Researcher, InfAI, Leipzig University, Germany
External Supervisor, University of Lubeck, Germany
DAAD Post-Doc-Net AI Fellow
General Chair *KGSWC-2023*
http://www.kgswc.org <http://www.kgswc.org/indo-american/>/
"Do what you love, Love what you do"