Summary of the paper
| Title | Expertise Mining for Enterprise Content Management |
|---|---|
| Authors | Georgeta Bordea, Sabrina Kirrane, Paul Buitelaar and Bianca Pereira |
| Abstract | Enterprise content analysis and platform configuration for enterprise content management is often carried out by external consultants that are not necessarily domain experts. In this paper, we propose a set of methods for automatic content analysis that allow users to gain a high level view of the enterprise content. Here, a main concern is the automatic identification of key stakeholders that should ideally be involved in analysis interviews. The proposed approach employs recent advances in term extraction, semantic term grounding, expert profiling and expert finding in an enterprise content management setting. Extracted terms are evaluated using human judges, while term grounding is evaluated using a manually created gold standard for the DBpedia datasource. |
| Topics | Information Extraction, Information Retrieval, Text mining, Semantic Web |
Full paper  |
Expertise Mining for Enterprise Content Management |
| Bibtex | @InProceedings{BORDEA12.379, author = {Georgeta Bordea and Sabrina Kirrane and Paul Buitelaar and Bianca Pereira}, title = {Expertise Mining for Enterprise Content Management}, 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} } |