[agents] [CFP] 1st International Workshop on Deep Learning for Question Answering @ KGSWC 2021

[Rim Hantach]

Dear colleagues and researchers,

Please consider submitting a paper for the 1st International workshop on
"Deep Learning for Question Answering" which will be held online - November
19-24, 2021.

*DLQA: **Deep Learning for Question Answering*

1st International Workshop, in conjunction with KGSWC 2021
<https://kgswc.org/>

November 19- 24, 2021 - Online

*https://kgswc.org/iwdlq2021/ <https://kgswc.org/iwdlq2021/>*

*Important dates:*
• Workshop paper submission due: October 01, 2021
• Workshop paper notifications: October 23, 2021
• Workshop paper camera-ready versions due: November 02, 2021
• Workshop: November 19-24, 2021 (half-day)



All deadlines are 23:59 anywhere on earth (UTC-12).

*Context of the workshop:*

Question Answering System (QAS) is an important area in Artificial
Intelligence.
Generating automatic response is a fastidious and time-consuming task for
there exists only some very general approaches to understand the intent of
users. Question Answering (QA) is applied in many domain applications such
as medical, finance, e-commerce, etc. Given a list of documents, a QAS can
provide the right answer to the query pose in natural language. It combines
natural language processing (NLP), information retrieval (IR) and knowledge
representation and reasoning (KRR) as a relevant component for this
process. The general process of QA is composed of different steps: (i) user
query, (ii) question analysis (simple or complex query, open or closed
domain, linguistic layer, semantic layer, etc), (iii) answer retrieval, and
(iv) answer extraction from a set of candidate ones. All these steps are
important to answer correctly, precisely and briefly to the user native
language question. The answer can refer to a term, a sentence, an image, an
audio, a video or to the full textual document.

Recent Deep Learning approaches and information retrieval are implemented
in order to reason over the questions and its links with the corresponding
response. Modern NLP techniques make it possible for computers to read and
interpret text, hear and understand speech, measure sentiment, and
determine which parts in a document are important. Another important aspect
of QAS is the integration of knowledge graphs (KGs) as a new dimension to
provide a concise answer issued from the KG. KG is graph-based data model
that structure and store real-world entities (abstract concepts) and their
relationships (hierarchical and associative) in a graph. The KG is the most
suitable and beneficial way to solve many challenging problems related to
information domain.

*Objective:*

The first edition of this workshop aims at highlighting recent and future
advances on
question answering systems over structured semantic and unstructured
textual data and to demonstrate the role of deep learning algorithms to
enrich this process. In addition to that, the goal of this workshop is to
bring together an area for experts from industry, science and academia to
exchange ideas and discuss results of on-going research in Question
Answering approaches.

*Topics of interests*:
• Question answering over Linked Data
• Knowledge Graphs for Question Answering
• Complex Question Answering over texts and linked data
• Reasoning for Complex Question Answering
• Natural Language Processing based question answering
• Hybrid text and knowledge graph reasoning
• SPARQL query pattern generation
• Natural language querying of RDF exposed as Linked Data
• Ontology-based query answering
• Visual Question Answering
• Image question answering
• Audio and Speech Question Answering
• Video Question Answering
• Datasets combining structured and unstructured knowledge
• Applications of question answering
• and so on.


*Submission:*

The workshop is open to submit unpublished work resulting from research
that presents original scientific results, methodological aspects, concepts
and approaches. All submissions are not anonymous and must be PDF documents
written in English and formatted using the following style files:
KGSWC2021_authors_kit
<http://www.springer.com/%20computer/lncs/lncs+authors?SGWID=0-40209-0-0-0?SGWID=0-40209-0-0-0>

Papers are to be submitted through the workshop's *EasyChair
<https://easychair.org/conferences/?conf=iwdlq2021>* submission page.

We welcome the following types of contributions:

   - *Full papers* (9-12 pages): Finished or consolidated R&D works, to be
   included in one of the Workshop topics.
   - *Short papers* (6-8 pages): Ongoing works with relevant preliminary
   results, opened to discussion.


Accepted papers are planned to publish with Springer Proceeding (Approval
Pending).

At least one author of each accepted paper must register for the workshop,
in order to present the paper. For further instructions, please refer to
the *KGSWC 2021 <https://kgswc.org/>* page.



*Workshop chairs:*Sarra Ben Abbès, Engie, France

Rim Hantach, Engie, France

Philippe Calvez, Engie, France
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