Abstract
Expert nding is one of the most rapidly developing IR
tasks and a popular research domain. The opportunity of
search for knowledgeable people in the scope of an organi-
zation or world-wide is a feature which makes modern En-
terprise search systems commercially successful and socially
demanded. A number of ecient expert nding approaches
was proposed recently. Despite that most of them are based
on theoretically sound measures of expertness, they still use
rather unrealistic and oversimplied principles. In our re-
search we try to avoid these limitations and come up with
models that go beyond the assumptions used in state-of-the-
art expert nding methods.
| Original language | Undefined |
|---|---|
| Title of host publication | Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (Doctoral Consortium), SIGIR 2008 |
| Place of Publication | New York |
| Publisher | Association for Computing Machinery |
| Pages | 893-893 |
| Number of pages | 1 |
| ISBN (Print) | 978-1-60558-164-4 |
| DOIs | |
| Publication status | Published - 20 Mar 2008 |
| Event | 31st Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2008 - Singapore, Singapore Duration: 20 Jul 2008 → 25 Jul 2008 Conference number: 31 |
Publication series
| Name | |
|---|---|
| Number | 1 |
Conference
| Conference | 31st Annual International ACM/SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2008 |
|---|---|
| Abbreviated title | SIGIR |
| Country/Territory | Singapore |
| City | Singapore |
| Period | 20/07/08 → 25/07/08 |
Keywords
- EWI-12312
- CR-H.3.3
- Enterprise search
- METIS-250965
- expertise search
- DB-IR: INFORMATION RETRIEVAL
- expert finding