Name
Title | ||
|---|---|---|
A Pseudo-relevance feedback framework combining relevance matching and semantic matching for information retrieval |
Abstract | ||
|---|---|---|
•Relevance matching plays a more important role than semantic matching in information retrieval.•The proposed framework, which combines relevance matching and semantic matching, is more effective than using either relevance matching or semantic matching.•Five enhanced models are generated by merging the framework with probability-based PRF models and language-model-based PRF models.•Our PRF framework combines relevance matching and semantic matching to improve the quality of the feedback documents. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ipm.2020.102342 | Information Processing & Management |
Keywords | DocType | Volume |
Information retrieval,Pseudo-relevance feedback,Text similarity,Semantic matching | Journal | 57 |
Issue | ISSN | Citations |
6 | 0306-4573 | 3 |
PageRank | References | Authors |
0.53 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Junmei Wang | 1 | 3 | 0.53 |
| Min Pan | 2 | 3 | 0.53 |
| Tingting He | 3 | 14 | 9.19 |
| Xiang Huang | 4 | 3 | 0.53 |
| Xueyan Wang | 5 | 3 | 0.53 |
| Xinhui Tu | 6 | 5 | 2.24 |