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

November 19- 24, 2021 - Online

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

Papers are to be submitted through the workshop's EasyChair 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 page.

Workshop chairs:
Sarra Ben Abbès, Engie, France

Rim Hantach, Engie, France

Philippe Calvez, Engie, France