Name
Title | ||
|---|---|---|
An Investigation of Relevance Feedback Using Adaptive Linear and Probabilistic Models. |
Abstract | ||
|---|---|---|
The SMART system (v. 11.0) was used as a front-end to a two-stage retrieval process. In the firststage, (WSJ) documents and the description field of (ad hoc) topics were indexed by the stems ofsingle terms; lnc and ltc weights were computed for word stems in documents and queries,respectively; and documents were ranked according to the cosine similarity of document and queryvectors. Related by the initial query vector, the first 5000 documents in the ranked list for eachtopic constituted a ... |
Year | Venue | Keywords |
|---|---|---|
1996 | TREC | indexation,probabilistic model,front end |
Field | DocType | Citations |
Data mining,Relevance feedback,Information retrieval,Ranking,Query expansion,Cosine similarity,Computer science,Linear model,Ranking (information retrieval),Statistical model,Probabilistic logic | Conference | 8 |
PageRank | References | Authors |
0.96 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert G. Sumner Jr. | 1 | 28 | 11.75 |
| William M. Shaw Jr. | 2 | 84 | 40.85 |