Abstract
Merging search results from different servers is a major problem in Distributed Information Retrieval. We used Regression-SVM and Ranking-SVM which would learn a function that merges results based on information that is readily available: i.e. the ranks, titles, summaries and URLs contained in the results pages. By not downloading additional information, such as the full document, we decrease bandwidth usage. CORI and Round Robin merging were used as our baselines; surprisingly, our results show that the SVM-methods do not improve over those baselines.
| Original language | Undefined |
|---|---|
| Title of host publication | The 10th Dutch-Belgian Information Retrieval Workshop |
| Place of Publication | Nijmegen |
| Publisher | Radboud University |
| Pages | 55-62 |
| Number of pages | 8 |
| ISBN (Print) | not assigned |
| Publication status | Published - 25 Jan 2010 |
| Event | 10th Dutch-Belgian Information Retrieval Workshop, DIR 2010 - Nijmegen, Netherlands Duration: 25 Jan 2010 → 25 Jan 2010 Conference number: 10 |
Publication series
| Name | |
|---|---|
| Publisher | Radboud University |
Conference
| Conference | 10th Dutch-Belgian Information Retrieval Workshop, DIR 2010 |
|---|---|
| Abbreviated title | DIR |
| Country/Territory | Netherlands |
| City | Nijmegen |
| Period | 25/01/10 → 25/01/10 |
Keywords
- Distributed Information Retrieval
- EWI-17664
- interleaving
- collection fusion
- learning to rank
- meta-search
- results merging
- IR-70344
- METIS-270757
- DB-IRNOX: INFORMATION RETRIEVAL (NON-XML)
- Federated search
- round robin