| |||||||||||||||
DOING@ADBIS 2023 : 4th International Workshop on Intelligent Data – From Data to Knowledge | |||||||||||||||
Link: https://www.univ-orleans.fr/lifo/evenements/doing/?page_id=995 | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
*****************************************************************************************
CALL FOR PAPERS DOING 2023: 4th International Workshop on Intelligent Data – From Data to Knowledge ***************************************************************************************** September 4, 2023 Barcelona In conjunction with ADBIS 2023 https://www.univ-orleans.fr/lifo/evenements/doing/?page_id=995 https://www.essi.upc.edu/dtim/ADBIS2023/ ******************************************************************************* IMPORTANT DATES ******************************************************************************* Paper submission: April 24, 2023 at 5 a.m. CET Notification of acceptance: May 15, 2023 Camera-ready due: June 9, 2023 Workshop day: September 4, 2023 ******************************************************************************* SUBMISSIONS ******************************************************************************* 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). ADBIS 2023 follows a Diversity and Inclusion policy that invites authors to adopt inclusive language in their papers and presentations (https://dbdni.github.io/pages/inclusivewriting.html and https://dbdni.github.io/pages/inclusivetalks.html). We also kindly ask all participants to adopt a proper code on conduct (https://dbdni.github.io/pages/codeofconduct.html). Accepted papers will be published in the Springer CCIS series and the best papers will be invited to a special issue of the Computer Science and Information Systems Journal (ISSN 2406-1018). Papers must be submitted via EASY CHAIR: https://easychair.org/my/conference?conf=doing2023 ******************************************************************************* AIMS AND SCOPE ******************************************************************************* 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. ******************************************************************************* TOPICS OF INTEREST ******************************************************************************* 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 ******************************************************************************* DOING workshop is connected to: DOING@MADICS: action in the MADICS network(https://www.madics.fr/actions/doing/) DOING@DIAMS: part of the RTR DIAMS (https://www.univ-orleans.fr/lifo/evenements/RTR-DIAMS/) ******************************************************************************* |
|