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CfP/OCS/ TI 2019 : CfP: Topical Issue on Intelligent Methods for Textual Information / Open Computer Science (ESCI, Scopus) / DE GRUYTER

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Link: https://www.degruyter.com/page/1831
 
When N/A
Where N/A
Submission Deadline TBD
Categories    information retrieval   machine learning   text mining   social media
 

Call For Papers

Topical Issue on Intelligent Methods for Textual Information Retrieval
www.degruyter.com/page/1831

Guest Editors:
Adrian-Gabriel Chifu, Aix-Marseille Université, France
Sébastien Fournier, Aix-Marseille Université, France

Advisory Editor:
Patrice Bellot, Aix-Marseille Université / CNRS, France

The deadline for submission is February 20, 2019, but individual papers will be reviewed and published online on an ongoing basis.
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We are pleased to announce that the new Topical Issue on Intelligent Methods for Textual Information Retrieval is now open for submission in Open Computer Science at DE GRUYTER. For more details please visit the Topical Issue website at www.degruyter.com/page/1831 or see a brief description appended below.

Open Computer Science is now indexed in SCOPUS and Web of Science Core Collection (Emerging Sources Citation Index). There are NO submission and publication FEES.
More information about the journal can be found at: https://www.degruyter.com/view/j/comp

DESCRIPTION

Machine learning approaches for intelligent text mining and retrieval are actively studied by researchers in natural language processing, information retrieval and other related fields. While supervised methods usually attain much better performance than unsupervised methods, they also require annotated data which is not always available or easy to obtain. Hence, we encourage the submission of supervised, unsupervised or hybrid methods for intelligent text retrieval tasks. Methods studying alternative learning paradigms, e.g. semi-supervised learning, weakly-supervised learning, zero-shot learning, but also transfer learning, are very welcome as well.

This thematic special issue covers three research areas: natural language processing, computational linguistics and information retrieval. The submissions may address, but are not limited to, the following topics:

• information retrieval
• information extraction
• query processing
• word sense disambiguation/discrimination
• machine learning in NLP
• sentiment analysis and opinion mining
• contradiction and controversy detection
• social media
• summarization
• text mining
• text categorization and clustering

The submitted papers will undergo peer review process before they can be accepted. Notification of acceptance will be communicated as we progress with the review process.

HOW TO SUBMIT

Before submission authors should carefully read the Instruction for Authors: https://www.degruyter.com/view/supplement/s22991093_Instruction_for_Authors.pdf

Manuscripts can be written in TeX, LaTeX (strongly recommended) − the journal’s LATEX template. Please note that we do not accept papers in Plain TEX format. Text files can be also submitted as standard DOCUMENT (.DOC) which is acceptable if the submission in LATEX is not possible. For an initial submission, the authors are strongly advised to upload their entire manuscript, including tables and figures, as a single PDF file.

All submissions to the Topical Issue must be made electronically via online submission system Editorial Manager: http://www.editorialmanager.com/opencs/
All manuscripts will undergo the standard peer-review process (single blind, at least two independent reviewers). When entering your submission via online submission system please choose the option “TI on Information Retrieval”.

Contributors to the Topical Issue will benefit from:

+ indexation in Web of Science (Emerging Sources Citation Index) and SCOPUS
+ NO submission and publication FEES
+ fair and constructive peer review provided by experts in the field
+ no space constraints + Convenient, web-based paper submission and tracking system – Editorial Manager
+ free language assistance for authors from non-English speaking regions
+ fast online publication upon completing the publishing process (continuous publication model)
+ better visibility due to Open Access to your article for all interested readers
+ long-term preservation of the content (all articles archived in Portico)
+ extensive post-publication promotion for selected papers

We are looking forward to your submission.
If you have any question, please contact Dr. Justyna Zuk, Managing Editor of Open Computer Science, Justyna.Zuk@degruyteropen.com.

With best regards,
Karolina Hejbudzka

***
Karolina Hejbudzka
Editorial Assistant, Physical Sciences.

DE GRUYTER

karolina.hejbudzka@degruyteropen.com
www.degruyter.com/openaccess

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Domicile Warsaw, Poland. Legal Form: Limited Company
Managing Director: Jacek Ciesielski

Newsletter and Alerts: www.degruyter.com/newsletter

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