Traditional information retrieval systems aim at satisfying most users for most of their searches, leaving aside the context in which the search takes place. We propose to model tw...
Nathalie Hernandez, Josiane Mothe, Claude Chrismen...
In classic InformationRetrieval systems a relevant document will not be retrieved in response to a query if the document and query representations do not share at least one term. T...
This paper presents a case-study of automatic construction of a hypertext from a large full-text document. The document we used as input of the automatic authoring process is a we...
We define the crouching Dirichlet, hidden Markov model (CDHMM), an HMM for partof-speech tagging which draws state prior distributions for each local document context. This simple...
Existing graph-based ranking methods for keyphrase extraction compute a single importance score for each word via a single random walk. Motivated by the fact that both documents a...
Zhiyuan Liu, Wenyi Huang, Yabin Zheng, Maosong Sun