Towards Text-Based Recommendations - Archive ouverte HAL Access content directly
Conference Papers Year : 2010

Towards Text-Based Recommendations


Recommender systems have become, like search engines, a tool that cannot be ignored by a website with a large selection of products, music, news or simply webpages. The performance of this kind of systems depends on a large amount of information. Meanwhile, the amount of information available in the Web is continuously growing. In this paper, we propose to provide recommendation from unstructured textual data. The method has two steps. First, subjective texts are labelled according to their expressed opinion. Second, the results are used to provide recommendations thanks to a collaborative filtering technique. We describe the complete processing chain and evaluate it.
Fichier principal
Vignette du fichier
RIAO_short_version.pdf (131.24 Ko) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-00470172 , version 1 (04-04-2010)


  • HAL Id : hal-00470172 , version 1


Damien Poirier, Isabelle Tellier, Françoise Fessant, Julien Schluth. Towards Text-Based Recommendations. RIAO 2010: 9th international conference on Adaptivity, Personalization and Fusion of Heterogeneous Information, Apr 2010, PARIS, France. pp.0-0. ⟨hal-00470172⟩
265 View
160 Download


Gmail Mastodon Facebook X LinkedIn More