Table 1 Supervised query expansion for biomedical information retrieval
From: A supervised term ranking model for diversity enhanced biomedical information retrieval
| Algorithm 1 supervised query expansion pipeline |
|---|
| Training the SQE model M |
| 1: For each training query q, select k candidate terms via PRF |
| 2: Label each term based on the diversity-oriented strategy |
| 3: Represent each term as a feature vector using different term features |
| 4: Train term ranking model M using the modified loss function |
| Testing the model M in query expansion retrieval |
| 1: For each testing query q, select k candidate terms via PRF |
| 2: Represent each term as a feature vector using the term features |
| 3: Apply M to obtain the top m terms for query expansion |
