Fiche du document
Date
23 janvier 2017
Type de document
Périmètre
Langue
Identifiants
- handle: 10670/1.839b3b
- hal: hal-02101479
Source
Collection
Organisation
Mots-clés
Hidden Markov Model - HMM Conditional random fields Data analysis and processing methods Analyse de données et data mining Chaine de Markov cachée Champ aléatoire conditionnel Décision de justice Analyse de données lexicalesSujets proches
Instruction and study--Methods Statistical data Cases, clinical reports, statistics Knowledge discovery in data Factual data analysis KDD (Information retrieval) Mining, Data Knowledge discovery in databases Algorithmic knowledge discovery Statistical data Statistical analysis Statistical methods Statistical science Natural science Sciences Science of science Fields, Random Law reporters (Publications) Court rulings Digests of cases (Law) Law reports, digests, etc.--Periodicals Court reports Court decisions Injustice Court rulings Court decisions Pattern Model Instruction and study--MethodsCiter ce document
Gildas Tagny Ngompe et al., « Detecting sections and entities in court decisions using HMM and CRF graphical models », HAL-SHS : linguistique, ID : 10670/1.839b3b
Métriques
Partage / Export
Résumé
International audience