Name
Abstract | ||
|---|---|---|
This work proposes an original combination of linguistic and structural descriptors to represent the content of biomedical papers. The objective is to show the effectiveness of descriptors taking into account the structure of documents to characterise three kinds of biomedical texts (reviews, research and clinical papers). The description of text is made at various levels, from the global level to the local one. The contexts makes it possible to characterise the three classes. The characterisation of the textual resources is carried out quantitatively by using the discriminating capacity of techniques of data mining based on emerging patterns. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1145/1166160.1166180 | ACM Symposium on Document Engineering |
Keywords | Field | DocType |
biomedical paper,biomedical literature,biomedical text,clinical paper,various level,structural descriptors,combining linguistic,original combination,global level,textual resource,text mining,data mining | Concept mining,Text mining,Information retrieval,Computer science,Biomedical text mining,Linguistics | Conference |
ISBN | Citations | PageRank |
1-59593-515-0 | 3 | 0.46 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nadia Zerida | 1 | 5 | 1.17 |
| Nadine Lucas | 2 | 36 | 8.30 |
| Bruno Crémilleux | 3 | 373 | 34.98 |