Name
Abstract | ||
|---|---|---|
This paper presents some experiments in clustering homogeneous XML documents to validate an existing classification or more generally an organisational structure. Our approach integrates techniques for extracting knowledge from docu- ments with unsupervised classification (clustering) of documents. We focus on the feature selection used for representing documents and its impact on the emerging clas- sification. We mix the selection of structured features with fine textual selection based on syntactic characteristics. We illustrate and evaluate this approach with a collection of Inria activity reports for the year 2003. The objective is to cluster projects into larger groups (Themes), based on the keywords or different chapters of these activity reports. We then compare the results of clustering using different feature selections, with the official theme structure used by Inria. |
Year | Venue | Keywords |
|---|---|---|
2005 | Clinical Orthopaedics and Related Research | categorisation,knowledge dis- covery,organisational structure,xml clustering,xml document,feature selection |
Field | DocType | Volume |
Data mining,Information retrieval,XML,Organizational structure,Feature selection,Homogeneous,Computer science,Typology,Knowledge extraction,Cluster analysis,Syntax | Journal | abs/cs/050 |
Citations | PageRank | References |
3 | 0.43 | 7 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Thierry Despeyroux | 1 | 139 | 26.04 |
| Yves Lechevallier | 2 | 333 | 33.02 |
| Brigitte Trousse | 3 | 404 | 52.87 |
| Anne-Marie Vercoustre | 4 | 331 | 81.83 |