33.2179, Calls: Applied Linguistics, Computational Linguistics, Discourse Analysis, Semantics, Syntax, Text/Corpus Linguistics / Information (Jrnl)

[The LINGUIST List]

LINGUIST List: Vol-33-2179. Sat Jul 02 2022. ISSN: 1069 - 4875.

Subject: 33.2179, Calls:  Applied Linguistics, Computational Linguistics, Discourse Analysis, Semantics, Syntax, Text/Corpus Linguistics / Information (Jrnl)

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Date: Sat, 02 Jul 2022 21:42:09
From: Jennifer D'Souza [jennifer.dsouza at tib.eu]
Subject: Applied Linguistics, Computational Linguistics, Discourse Analysis, Semantics, Syntax, Text/Corpus Linguistics / Information (Jrnl)

 
Full Title: Information 


Linguistic Field(s): Applied Linguistics; Computational Linguistics; Discourse Analysis; Semantics; Syntax; Text/Corpus Linguistics 

Subject Language(s): English (eng)

Call Deadline: 10-Dec-2022 

Call for Papers:

Dear Colleagues and Friends,

We have organized a Special Issue on ''Information Extraction and Language
Discourse Processing.'' Below is the relevant background for this SI outlining
its scope.

Information extraction (IE) plays an increasingly important and pervasive role
in today’s era of digitalized communication media based on the Semantic Web.
E.g., search engine results, as snippets, are slowly replaced by “rich
snippets”; there is an interest in converting scholarly publications to
structured records available in such downstream IT applications as
Leaderboards, etc. IE is thus the task of automatically extracting structured
information from unstructured and/or semi-structured electronically
represented documents. In most cases, this activity concerns processing of
human language texts by means of natural language processing (NLP). The
automatic extraction of information from unstructured sources has opened up
new avenues for querying, organizing, and analyzing data by drawing upon the
clean semantics of structured databases and the abundance of unstructured
data.

Apart from extrinsic models of IE, research in linguistics and computational
linguistics have long pointed out that text is not just simple sequence of
clauses and sentences but rather follows a highly elaborated structure
formalized within discourse. The framework used for discourse analysis has
long since been rhetorical structure theory (RST). Within a well-written text,
no unit of the text is completely isolated; interpretation requires
understanding the unit’s relation with the context. Research in discourse
analysis aims to unmask such relations in the text, which is helpful for many
downstream applications such as summarization, information retrieval, and
question answering.

This Special Issue seeks novel research reports on the spectrum that blends
information extraction and language discourse processing research in diverse
communities. The editors welcome submissions along various dimensions derived
from the nature of the extraction task, the advanced neural techniques used
for extraction, the variety of input resources exploited, and the type of
output produced. Quantitative, qualitative, and mixed methods studies are
welcome, as are case studies and experience reports if they describe an
impactful application at a scale that delivers useful lessons to the journal
readership.

Topics of interest include (but are not limited to):

- Knowledge base population with discourse-centric information extraction (IE)
- Coreference resolution and its impact on discourse-centric IE
- Relationship extraction leveraging linguistic discourse
- Template filling
- Impact of pragmatics or rhetorics on information extraction
- Discourse-centric IE at scale
- Intelligent and novel assessment models of discourse-centric IE
- Survey of discourse-centric IE in natural language processing (NLP)
- Challenges implementing discourse-centric IE in real-world scenarios
- Modeling domains using discourse-centric IE
- Human–AI hybrid systems for learning discourse and IE

Please find the online portal for the SI with submission instructions here
https://www.mdpi.com/journal/information/special_issues/WYS02U2GTD  

Yours cordially,
Dr. Jennifer D'Souza
Prof. Dr. Chengzhi Zhang
Guest Editors




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