Name
Abstract | ||
|---|---|---|
Information retrieval systems typically weight the importance of search terms according todocument and collection statistics (such as by using tf \Theta idf scores, where less common termsare given higher weight). We consider here the scenario where a user can express her ownsubjective weighting of the importance of the terms that form the query on top of the systemgeneratedweighting, and show how this should modify the relevance scores of documents.This has been allowed before, but... |
Year | Venue | Keywords |
|---|---|---|
2000 | RIAO | information retrieval system |
Field | DocType | Citations |
Weighting,Ranking,Information retrieval,Query expansion,Computer science,Response time,Heuristics,Ranking (information retrieval),Artificial intelligence,Machine learning | Conference | 10 |
PageRank | References | Authors |
0.72 | 9 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ronald Fagin | 1 | 8808 | 2643.66 |
| Yoëlle S. Maarek | 2 | 361 | 69.41 |