TEXT2KG 2022 : International Workshop on Knowledge Graph Generation from Text
Call For Papers
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.
Topics of Interest:
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
Paper submissions due: February 28th, 2022
Final decision notification: March 28th, 2022
Camera-ready submissions due: April 11th, 2022
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 ESWC conference, and they will be published as Springer’s Lecture Notes in Computer Science series. Papers are to be 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.
Submission Link: https://easychair.org/conferences/?conf=text2kg
Sanju Tiwari (email@example.com)
Sanju Tiwari, UAT Mexico
Nandana Mihindukulasooriya, MIT-IBM Watson AI Lab, USA
Francesco Osborne, KMi, The Open University
Dimitris Kontokostas, Diffbot, Greece
Jennifer D’Souza, TIB – Leibniz Information Centre for Science and Technology and University Library, Germany
Mayank Kejriwal, University of Southern California, USA
Steering Committee & Publicity Chair:
Amit Sheth, University of South Carolina, USA
Joey Yip, University of South Carolina, USA
Sören Auer, Leibniz University of Hannover and TIB, Germany
Enrico Motta, The Open University, United Kingdom
Anna Fensel, Wageningen University & Research & University of Innsbruck, Austria
Maria Esther Vidal, Leibniz University of Hannover and TIB, Germany
Fernando Ortiz-Rodriguez, Universidad Autonoma de Tamaulipas, Mexico
Sven Groppe, University of Lubeck, Germany