F
Fadi Badra
Researcher at French Institute for Research in Computer Science and Automation
Publications - 30
Citations - 344
Fadi Badra is an academic researcher from French Institute for Research in Computer Science and Automation. The author has contributed to research in topics: Knowledge acquisition & Knowledge extraction. The author has an hindex of 9, co-authored 25 publications receiving 307 citations. Previous affiliations of Fadi Badra include French Institute of Health and Medical Research & Digital Enterprise Research Institute.
Papers
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Proceedings Article
Case base mining for adaptation knowledge acquisition
TL;DR: An approach to AKA based on the principles and techniques of knowledge discovery from databases and data-mining is presented, implemented in CABAMAKA, a system that explores the variations within the case base to elicit adaptation knowledge.
TAAABLE: Text Mining, Ontology Engineering, and Hierarchical Classification for Textual Case-Based Cooking
Fadi Badra,Rokia Bendaoud,Rim Bentebibel,Pierre-Antoine Champin,Julien Cojan,Amélie Cordier,Sylvie Desprès,Stéphanie Jean-Daubias,Jean Lieber,Thomas Meilender,Alain Mille,Emmanuel Nauer,Amedeo Napoli,Yannick Toussaint +13 more
TL;DR: This paper presents how the Taaable project addresses the textual case-based reasoning challenge of the CCC, thanks to a combination of principles, methods, and technologies of various fields of knowledge-based system technologies.
Book ChapterDOI
Taaable: A Case-Based System for Personalized Cooking
Amélie Cordier,Valmi Dufour-Lussier,Jean Lieber,Emmanuel Nauer,Fadi Badra,Julien Cojan,Emmanuelle Gaillard,Laura Infante-Blanco,Pascal Molli,Amedeo Napoli,Hala Skaf-Molli +10 more
TL;DR: This chapter describes TAAABLE and its modules, including the CBR engine and features such as the retrieval process based on minimal generalization of a query and the different adaptation processes available, and focuses on the knowledge containers used by the system.
Proceedings Article
Knowledge Acquisition and Discovery for the Textual Case-Based Cooking system WIKITAAABLE
Fadi Badra,Julien Cojan,Amélie Cordier,Jean Lieber,Thomas Meilender,Alain Mille,Pascal Molli,Emmanuel Nauer,Amedeo Napoli,Hala Skaf-Molli,Yannick Toussaint +10 more
TL;DR: The textual case-based cooking system WIKITAAABLE participates to the second Computer cooking contest (CCC) and opportunistic adaptation knowledge discovery is an approach for interactive and semi-automatic learning of adaptation knowledge triggered by a feedback from the user.
Book ChapterDOI
Opportunistic Adaptation Knowledge Discovery
TL;DR: In this paper, two strategies are combined in order to reduce the knowledge engineering cost induced by the adaptation knowledge (AK) acquisition task: AK is learned from the case base by the means of knowledge discovery techniques, and the AK acquisition sessions are opportunistically triggered, i.e., at problem-solving time.