[AISWorld] CFP - 24th International Conference on Applications of Natural Language to Information Systems (NLDB 2019)

Vijayan Sugumaran sugumara at oakland.edu
Mon Oct 15 14:56:22 EDT 2018

Call for Papers NLDB 2019
24th  International Conference on Applications of Natural Language to
Information Systems

26-28 June 2019, University of Salford, MediaCityUK Campus, United Kingdom

 <http://nldb.org/> http://nldb.org/

Important Dates:

Full paper submission: 1 March 2019
Notification of acceptance: 01 April 2019
Camera-ready papers: 15 April 2019
Conference: 26-28 June 2019

Since 1995, the NLDB conference aims at bringing together researchers,
industrials and potential users interested in various applications of
Natural Language in the Database and Information Systems field. NLDB 2019
invites researchers from academia and industry to submit papers for oral or
poster presentations on recent, unpublished research that addresses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 review and discussion papers.

Topics of interest include but are not limited to:

Argumentation Mining and Applications: Automatic detection of argumentation
components and relationships, Creation of resources, e.g. annotated corpora,
treebanks and parsers, Integration of NLP techniques with formal, Abstract
argumentation structures, Argumentation Mining from legal texts and
scientific articles, Applications, e.g. in opinion mining/sentiment analysis

Deep Learning, Neural Languages and NLP: Word2Vec applications, e.g. opinion
mining, text summarization, machine translation, Development of novel deep
learning architectures and algorithms, Parallel computation techniques and
GPU programming for neural language models

Social Media and Web Analytics: Plagiarism detection, Opinion
mining/sentiment analysis, detection of fake reviews, Information
extraction: NER, event detection, term and semantic relationship extraction,
Text summarization, Text classification and clustering, Corpus analysis,
Language detection, Robust NLP methods for sparse, ill-formed texts,
Recommendation systems

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

Corpus Analysis: Multi-lingual and Multi-cultural corpus, Machine
translation, Text analysis, Classification systems, Extraction, Named Entity
and Event Extraction

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 Modeling: 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, NLP techniques for Internet of Things
(IoT), NLP techniques for ambient intelligence

Big Data and Business intelligence: Identity Detection, Semantic Data
cleaning, Summarisation, Reporting.


Submission Guidelines:

Authors should submit manuscripts via the NLDB 2019 web submission system
using easychair at: https://easychair.org/conferences/?conf=nldb2019 


Accepted formats are: PostScript or Portable Document Format (PDF). Papers
should not exceed 12 pages. The Proceedings of NLDB 2019 will be published
in the LNCS-series at Springer Verlag. The authors should follow the LNCS
format ( <http://www.springer.de/comp/lncs/authors.html>

The best papers will be selected after the conference and an extended
version of these papers will be published in the Data and Knowledge
Engineering Journal (Elsevier) as a special issue


Vijayan Sugumaran, Ph.D.

Professor of 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:  <mailto:sugumara at oakland.edu> sugumara at oakland.edu




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