Clustering and Relational Ambiguity: from Text Data to Natural Data - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Data Mining and Digital Humanities Année : 2013

Clustering and Relational Ambiguity: from Text Data to Natural Data

Nicolas Turenne

Résumé

Text data is often seen as "take-away" materials with little noise and easy to process information. Main questions are how to get data and transform them into a good document format. But data can be sensitive to noise oftenly called ambiguities. Ambiguities are aware from a long time, mainly because polysemy is obvious in language and context is required to remove uncertainty. I claim in this paper that syntactic context is not suffisant to improve interpretation. In this paper I try to explain that firstly noise can come from natural data themselves, even involving high technology, secondly texts, seen as verified but meaningless, can spoil content of a corpus; it may lead to contradictions and background noise.
Fichier principal
Vignette du fichier
JDMDH_turenne.pdf (1.3 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00920423 , version 1 (19-12-2013)

Identifiants

  • HAL Id : hal-00920423 , version 1
  • PRODINRA : 244029

Citer

Nicolas Turenne. Clustering and Relational Ambiguity: from Text Data to Natural Data. Journal of Data Mining and Digital Humanities, 2013, 1 (1), pp.1. ⟨hal-00920423⟩
106 Consultations
172 Téléchargements

Partager

Gmail Facebook X LinkedIn More