Run
| RanxHub ID: | amdbfpse/cs/test/ikr3/bm25-bienc-qa |
|---|---|
| Version: | 1.0 |
| Description: | This run was computed using BiEnc and QA to re-rank the top 1000 BM25 results. Original and re-ranking scores were fused using the Weighted Sum fusion algorithm provided by ranx. |
| Tags: | Fine-Tuned · Re-Ranking |
| Date: | 12 August 2022 |
| Run Authors: | Elias Bassani |
| From Paper: | A Multi-Domain Benchmark for Personalized Search Evaluation |
| Paper Authors: | Elias Bassani · Pranav Kasela · Alessandro Raganato · Gabriella Pasi |
Model
| Name: | BiEnc / QA |
|---|---|
| Description: | BiEnc is a bi-encoder retrieval model. QA is a query-aware personalization model that weighs the contribution of the user-related texts w.r.t. the query during personalization. Texts representations were computed with all-MiniLM-L6-v2. |
| Tags: | Personalization · Long-Term Personalization · Neural Network · Deep Learning · Transformer |
| Paper: | A Multi-Domain Benchmark for Personalized Search Evaluation |
| Authors: | Elias Bassani · Pranav Kasela · Alessandro Raganato · Gabriella Pasi |
Results
| MAP@100 | MRR@10 | NDCG@10 |
|---|---|---|
| 0.2011139936470018 | 0.611702226424406 | 0.3114890530969009 |