ICON 2021 : 18th International Conference on Natural Language Processing
Call For Papers
The eighteenth International Conference on Natural Language Processing (ICON-2021) will be held at NIT Silchar, India during December 16-19, 2021. The ICON Conference series is a forum for promoting interaction among researchers in the field of Natural Language Processing (NLP) and Computational linguistics (CL) in India and abroad. The main conference is on December 17-18, 2021. This will be preceded by one day of pre-conference tutorials / workshops on December 16, 2021 and one day of post conference shared tasks / tools / demos on December 19, 2021.
Topics of interest include but are not limited to, the following
Named Entity Recognition
Sentiment and Emotion Analysis
Natural Language Generation
Information Retrieval and Text Mining
NLP for Digital Humanities
Ethics in NLP
NLP for Education
NLP Language Documentation and Preservation
Machine Learning Applications to NLP
Cognitive Modelling and Psycholinguistics
Interpretability and Explainibility of NLP models
Computational Social Science and Social Media
Paper Submission Information
Long paper submissions must describe substantial, original, completed and unpublished work.
Long papers may consist of up to 8 pages of content, plus unlimited references. Finalversions of long papers will be given one additional page of content (up to 9 pages) plus any no of pages for the references.
Short paper submissions must describe original and unpublished work. Please note that a short paper is not a shortened long paper. Instead short papers should have a point that can be made in a few pages. Some kinds of short papers are:
A small, focused contribution
A negative result
An opinion piece
An interesting application nugget
Short papers may consist of up to 4 pages of content, plus unlimited references. Upon acceptance, short papers will be given 5 content pages in the proceedings.
Authors are encouraged to use this additional page to address reviewers' comments in their final versions.
Instructions for Double-Blind Review
As reviewing will be double blind, papers must not include authors' names and affiliations. Furthermore, self-references or links (such as github) that reveal the author's identity, e.g., "We previously showed (Smith, 1991) .." must be avoided. Instead, use citations such as "Smith previously showed (Smith, 1991) ..." Papers that do not conform to these requirements will be rejected without review.
Papers should not refer, for further detail, to documents that are not available to the reviewers. For example, do not omit or redact important citation information to preserve anonymity. Instead, use third person or named reference to this work, as described above ("Smith showed" rather than "we showed").
Papers may be accompanied by a resource (software and/or data) described in the paper, but these resources should be anonymized as well.