[AISWorld] CFP - International Conference on Natural Language & Information Systems (NLDB 2023)

[Vijayan Sugumaran]

NLDB 2023

The 28th International Conference on Natural Language & Information Systems

21-23 June 2023, University of Derby, United Kingdom.

https://www.derby.ac.uk/events/latest-events/nldb-2023/ 

 

Conference Chairs:

Warren Manning, University of Derby, UK

Elisabeth Métais, Conservatoire des Arts et Métiers, Paris, France

Farid Meziane, University of Derby, UK

 

Program Chairs:

Stephan Reiff-Marganiec, University of Derby, UK

Vijayan Sugumaran, Oakland University, Rochester, USA

 

About NLDB

The 28th International Conference on Natural Language & Information Systems
will be held at the University of Derby, United Kingdom and will be a face
to face event. Since 1995, the NLDB conference brings together researchers,
industry practitioners, and potential users interested in various
application of Natural Language in the Database and Information Systems
field. The term "Information Systems" has to be considered in the broader
sense of Information and Communication Systems, including Big Data, Linked
Data and Social Networks.

 

The field of Natural Language Processing (NLP) has itself recently
experienced several exciting developments. In research, these developments
have been reflected in the emergence of neural language models (Deep
Learning, Word Embeddings, Transformers) and the importance of aspects such
as transparency, bias and fairness, a (renewed) interest in various
linguistic phenomena, such as in discourse and argumentation mining, and in
new problems such as the detection of disinformation and hate speech in
social media, as well of mental health disorders that increased during the
recent pandemic. Regarding applications, NLP systems have evolved to the
point that they now offer real-life, tangible benefits to enterprises. Many
of these NLP systems are now considered a de-facto offering in business
intelligence suites, such as algorithms for recommender systems and opinion
mining/sentiment analysis.

 

It is against this backdrop of recent innovations in NLP and its
applications in information systems that the 28th edition of the NLDB
conference takes place. We welcome research and industrial contributions,
describing novel, previously unpublished works on NLP and its applications
across a plethora of topics as described in the Call for Papers.

 

Call for Papers

NLDB 2023 invites authors to submit papers for oral or poster presentations
on unpublished research that addresses theoretical aspects, algorithms,
applications, architectures for applied and integrated NLP, resources for
applied NLP, and other aspects of NLP, as well as survey and discussion
papers. This year's edition of NLDB also introduces an Industry Track, to
foster fruitful interaction between the industry and the research community.


 

Topics of interest include but are not limited to:

*	Social Media and Web Analytics: Opinion mining/sentiment analysis,
irony/sarcasm detection; detection of fake reviews and deceptive language;
detection of harmful information: fake news and hate speech; sexism and
misogyny; detection of mental health disorders; identification of
stereotypes and social biases; robust NLP methods for sparse, ill-formed
texts; recommendation systems.
*	Deep Learning and eXplainable Artificial Intelligence (XAI): Deep
learning architectures, word embeddings, transparency, interpretability,
fairness, debiasing, ethics.

*	Argumentation Mining and Applications: Automatic detection of
argumentation components and relationships; creation of resource (e.g.
annotated corpora, treebanks and parsers); Integration of NLP techniques
with formal, abstract argumentation structures; Argumentation Mining from
legal texts and scientific articles.
*	Question Answering (QA): Natural language interfaces to databases,
QA using web data, multi-lingual QA, non-factoid QA(how/why/opinion
questions, lists), geographical QA, QA corpora and training sets, QA over
linked data (QALD).
*	Corpus Analysis: multi-lingual, multi-cultural and multi-modal
corpora; machine translation, text analysis, text classification and
clustering; language identification; plagiarism detection; information
extraction: named entity, extraction of events, terms and semantic
relationships.
*	Semantic Web, Open Linked Data, and Ontologies: Ontology learning
and alignment, ontology population, ontology evaluation, querying ontologies
and linked data, semantic tagging and classification, ontology-driven NLP,
ontology-driven systems integration.
*	Natural Language in Conceptual Modelling: Analysis of natural
language descriptions, NLP in requirement engineering, terminological
ontologies, consistency checking, metadata creation and harvesting.
*	Natural Language and Ubiquitous Computing: Pervasive computing,
embedded, robotic and mobile applications; conversational agents; NLP
techniques for Internet of Things (IoT); NLP techniques for ambient
intelligence
*	Big Data and Business Intelligence: Identity detection, semantic
data cleaning, summarization, reporting, and data to text.

Important Dates

Full paper submission: 14 March, 2023

Paper notification: 10 April, 2023

Camera-ready deadline: 24 April, 2023

Conference: 21-23 June 2023

 

Submission Guidelines

Authors should follow the LNCS format
(https://www.springer.com/gp/computer-science/lncs/conference-proceedings-gu
idelines) and submit their manuscripts in pdf via Easychair
(https://easychair.org/conferences/?conf=nldb2023 )

 

Submissions can be full papers (12 pages maximum including references),
short papers (8 pages including references) or papers for a poster
presentation or system demonstration (6 pages including references). The
program committee may decide to accept some full papers as short papers or
poster papers.

 

The reviewing process of NLDB 2023 is double-blind, i.e., submissions to the
main conference and to the industry track must not contain author names or
other identifying information, such as funding sources, acknowledgments and
must use the third person to refer to work the authors have previously
undertaken. System demonstration papers may not be anonymous.

 

================================================

Vijayan Sugumaran, Ph.D.

Distinguished Professor, Management Information Systems

Chair, Department of Decision and Information Sciences

Co-Director, Center for Data Science and Big Data Analytics

School of Business Administration

Oakland University

Rochester, MI 48309

Phone: 248-370-4649

Fax: 248-370-4275

Email: sugumara at oakland.edu <mailto:sugumara at oakland.edu> 

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