Name
Abstract | ||
|---|---|---|
While the public has increasingly access to medical information, specialized medical language is often difficult for non-experts to understand and there is a need to bridge the gap between specialized language and lay language. As a first step towards this end, we describe here a method to build a comparable corpus of expert and non-expert medical French documents and to identify similar text segments of lay and specialized language. Among the top 400 pairs of text segments retrieved with this method, 59% were actually similar and 37% were deemed exploitable for further processing. This is encouraging evidence for the target task of finding equivalent expressions between these two varieties of language. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.3233/978-1-58603-864-9-89 | Studies in Health Technology and Informatics |
Keywords | Field | DocType |
Natural Language Processing,Consumer Vocabulary,Comparable Corpora | Expression (mathematics),Computer science,Artificial intelligence,Natural language processing,Unified Medical Language System | Conference |
Volume | ISSN | Citations |
136 | 0926-9630 | 1 |
PageRank | References | Authors |
0.39 | 13 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Louise Deleger | 1 | 234 | 20.13 |
| Pierre Zweigenbaum | 2 | 773 | 85.43 |