Summary of the paper
| Title | Irregularity Detection in Categorized Document Corpora |
|---|---|
| Authors | Borut Sluban, Senja Pollak, Roel Coesemans and Nada Lavrac |
| Abstract | The paper presents an approach to extract irregularities in document corpora, where the documents originate from different sources and the analyst's interest is to find documents which are atypical for the given source. The main contribution of the paper is a voting-based approach to irregularity detection and its evaluation on a collection of newspaper articles from two sources: Western (UK and US) and local (Kenyan) media. The evaluation of a domain expert proves that the method is very effective in uncovering interesting irregularities in categorized document corpora. |
| Topics | Knowledge Discovery/Representation, Statistical and machine learning methods, Text mining |
Full paper  |
Irregularity Detection in Categorized Document Corpora |
| Bibtex | @InProceedings{SLUBAN12.706, author = {Borut Sluban and Senja Pollak and Roel Coesemans and Nada Lavrac}, title = {Irregularity Detection in Categorized Document Corpora}, booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)}, year = {2012}, month = {may}, date = {23-25}, address = {Istanbul, Turkey}, editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Uğur Doğan and Bente Maegaard and Joseph Mariani and Asuncion Moreno and Jan Odijk and Stelios Piperidis}, publisher = {European Language Resources Association (ELRA)}, isbn = {978-2-9517408-7-7}, language = {english} } |