Name
Abstract | ||
|---|---|---|
We investigate the creation of a robust algorithm for document identification and page ordering in a digital mail room in the banking sector. PaperClip is a system that takes dossiers containing pages of various documents as input, and returns multiple files that contain all the pages of one document in the correct order. PaperClip performs (1) document type classification and (2) page number classification on each page, and then (3) merges the results. We experimented with various algorithms and methods for these three steps and we performed an elaborate evaluation to measure different aspects of the methods. The best performing setup achieved a cut F-score of 86% and a V-measure of 0.91%. This performance is sufficient to fulfill business needs of the banking sector. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.5220/0006195904710478 | ICPRAM: PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION APPLICATIONS AND METHODS |
Keywords | Field | DocType |
Dossier Reorganizing, Text Classification, Pagenumber Classification, Customer Document Processing | Computer science,Human–computer interaction,Artificial intelligence,Machine learning | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wessel Stoop | 1 | 0 | 1.69 |
| Iris Hendrickx | 2 | 285 | 30.91 |
| Tom van Ees | 3 | 0 | 0.34 |