Name
Title | ||
|---|---|---|
PILLS: Multilingual generation of medical information documents with overlapping content |
Abstract | ||
|---|---|---|
In the pharmaceutical industry, products have to be described by a range of document types with overlapping content. Moreover, much of this documentation has to be produced in many languages. This situation is commonplace in many commercial domains, and leads to well-known problems in maintaining a set of related documents and their translations. We describe a potential solution explored in the PILLS project. All relevant knowledge about a product is entered only once, through a natural-language interface to a knowledge base. From this 'master model', specialised models for a range of document types are derived automatically; from each specialised model, documents are generated automatically in all supported languages. As an illustration of this approach, the PILLS demonstrator generates three medical document types in English, German and French. |
Year | Venue | Keywords |
|---|---|---|
2002 | LREC | knowledge base,natural language interface |
Field | DocType | Citations |
Natural language generation,Pharmaceutical industry,Computer science,Artificial intelligence,Natural language processing,Knowledge base,Documentation,German | Conference | 14 |
PageRank | References | Authors |
1.02 | 3 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nadjet Bouayad-Agha | 1 | 206 | 20.28 |
| Richard Power | 2 | 486 | 45.19 |
| Donia Scott | 3 | 634 | 71.58 |
| Anja Belz | 4 | 482 | 41.74 |