CFP: INTERNATIONAL WORKSHOP ON KNOWLEDGE GRAPH GENERATION FROM TEXT (TEXT2KG)

###Apologies for cross Postings###INTERNATIONAL WORKSHOP ON KNOWLEDGE GRAPH
GENERATION FROM TEXT (TEXT2KG)

KNOWLEDGE GRAPH GENERATION

Knowledge Graphs are getting traction in both academia and in the industry
as one of the key elements of AI applications. They are being recognized as
an important and essential resource in many downstream tasks such as
question answering, recommendation, personal assistants, business
analytics, business automation, etc. Even though there are large knowledge
graphs built with crowdsourcing such as Wikidata or using semi-structured
data such as DBpedia or Yago or from structured data such as relational
databases, building knowledge graphs from text corpora still remains an
open challenge.

The workshop welcomes a broad range of papers including full research
papers, negative results, position papers, dataset, and system demos
examining the wide range of issues and processes related to knowledge
graphs generation from text corpora including, but not limited to entity
linking, relation extraction, knowledge representation, and Semantic Web.
Papers on resources (methods, tools, benchmarks, libraries, datasets) are
also welcomed.

One best paper will be selected for a prize with an industrial sponsor.

*Why attend the Text2KG Workshop?*

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), 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, Nanopublications), 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.
Theme and Topics

   -  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

IMPORTANT DATES

Paper submissions due: February 28th, 2022
Final decision notification: March 28th, 2022
Camera-ready submissions due: April 11th, 2022
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
<https://easychair.org/conferences/?conf=text2kg> 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 Springer’s *Lecture
Notes in Computer Science series* <https://2022.eswc-conferences.org/>.
All must be submitted, and formatted in the style of the Springer
Publications format for Lecture Notes in Computer Science (LNCS).
For details on the LNCS style, see Springer’s Author Instructions
<https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines>
.

*Submission Link:* https://easychair.org/conferences/?conf=text2kg

*Workshop Link: *https://aiisc.ai/text2kg/

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



*Organizing Chairs:*

Sanju Tiwari, UAT Mexico,  tiwarisanju18@ieee.org

Nandana Mihindukulasooriya, MIT-IBM Watson AI Lab, USA <nandana.m@ibm.com>

Francesco Osborne, KMi, The Open University <francesco.osborne@open.ac.uk>

Dimitris Kontokostas, Diffbot, Greece <dimitris@diffbot.com>
Jennifer D’Souza, TIB, Germany, <jennifer.dsouza@tib.eu>

Mayank Kejriwal, University of Southern California, USA,
mayankkejriwal@utexas.edu



*Publicity Chair:*

Joey Yip, University of South Carolina, USA, joey@knoesis.org

-- 
Regards
Dr. Sanju Tiwari (PhD, Post-Doc), SMIEEE
Sr. Researcher, Universidad Autonoma de Tamaulipas, Mexico
Adjunct Professor, Vardhaman College of Engineering, Hyderabad, India
DAAD Post-Doc-Net AI Fellow
General Chair *KGSWC-2021* (Second Indo-American Conference)
http://www.kgswc.org/indo-american/

"Do what you love, Love what you do"