5th International Workshop on Intelligent Data – From Data to Knowledge

When:
28/08/2024 all-day
2024-08-28T02:00:00+02:00
2024-08-28T02:00:00+02:00

Date : 2024-08-28
Lieu : Bayonne, France

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CALL FOR PAPERS
DOING 2024: 5th International Workshop on Intelligent Data – From Data to Knowledge
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August 28, 2024
Bayonne, France

In conjunction with ADBIS 2024

DOING@ADBIS 2024

Home – Technology Event

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IMPORTANT DATES
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Paper submission: 29 April, 2024 at 5 a.m. CET
Notification of acceptance: 8 June , 2024
Camera-ready due: 18 June , 2024
Workshop day: 8 August , 2024

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SUBMISSIONS
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DOING workshop accepts short (limited to 6-8 pages) and long (limited to 12 pages) papers. DOING reserves the right to accept as short papers those submitted as long, describing interesting and innovative ideas but still requiring further technical development. Papers should be written in English, formatted in Latex and present substantially original results. We adopt a double blind review policy: the papers submitted for review MUST NOT contain the authors’ names, affiliations, or any information that may disclose the authors’ identity. Authors should consult Springer’s authors’ guidelines and use their proceedings templates (you can download the templates available on the bottom of that page).

The workshop papers will be published by Springer in Communications in Computer and Information Science (CCIS). The authors of selected workshop papers will be invited to submit an extended version of their contributions to a special issue of an international journal.

ADBIS 2024 continues to participate in the Diversity and Inclusion (D&I) initiative of the Database community aiming to guide researchers in our community to adopt a more inclusive mindset in general toward different individuals.

**** Papers must be submitted via EASY CHAIR: https://easychair.org/conferences/?conf=adbis2024

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AIMS AND SCOPE
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The workshop focuses on transforming data into information and then into knowledge. The idea is to gather researchers to discuss two main problems :

how to extract information from textual data and represent it in knowledge bases;
how to propose intelligent methods for handling and maintaining these databases with new forms of requests, including efficient, flexible, and secure analysis mechanisms, adapted to the user, and with quality and privacy preservation guarantees.

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TOPICS OF INTEREST
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We invite the submission of work-in-progress that address various aspects of information extraction from textual data, intelligent and efficient interrogation, and maintenance of (large) knowledge bases. The workshop welcomes submissions of theoretical, technical, experimental, methodological papers, application papers, position papers and papers on experience reports addressing – though not limited to – the following topics:

Artificial intelligence in databases and information systems
Data curation, annotation, and provenance
Data management and analytics
Data mining and knowledge discovery
Data models and query languages
Data quality and data cleansing
Data science (theory and techniques)
Context-aware and adaptive information systems
Constraints extraction from text
Natural language processing
Indexing, query processing and optimization
Information and knowledge extraction
Information integration
Information quality
Graph databases
Knowledge bases (querying, management, evolution and dynamics)
Machine learning for knowledge graph construction, completion, refinement
Machine learning for knowledge and information extraction, for instance, named entity disambiguation, sentiment analysis, relation extraction, or the detection of claims, facts and stances from unstructured documents
Machine Learning in NLP
Management of large volumes of data
Methodologies, models, algorithms, and architectures for applied data science
NLP for Digital Humanities
NLP & Knowledge Graphs
Privacy, trust and security in databases
Query processing and optimization
Question answering over knowledge graphs
Text databases

Preferred Application Domains (but not limited to).

Bio-sciences and healthcare
Environmental issues

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