Syst\`emes du LIA \`a DEFT'13
Xavier Bost, Ilaria Brunetti, Luis Adri\'an Cabrera-Diego,, Jean-Val\`ere Cossu, Andr\'ea Linhares, Mohamed Morchid, Juan-Manuel, Torres-Moreno, Marc El-B\`eze, Richard Dufour

TL;DR
This paper describes the LIA systems developed for the 2013 DEFT campaign, focusing on document classification and information extraction in the culinary domain, demonstrating promising results despite task complexity.
Contribution
The paper introduces specialized systems for text classification and information extraction in recipes, tailored for the DEFT 2013 challenge.
Findings
Systems achieved promising results in complex tasks
Effective methods for domain-specific text analysis
Demonstrated adaptability to specialized language tasks
Abstract
The 2013 D\'efi de Fouille de Textes (DEFT) campaign is interested in two types of language analysis tasks, the document classification and the information extraction in the specialized domain of cuisine recipes. We present the systems that the LIA has used in DEFT 2013. Our systems show interesting results, even though the complexity of the proposed tasks.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNatural Language Processing Techniques
