# Reranking Algorithm

A reranking algorithm is an algorithm that reranks the outputs of a ranking algorithm.

**AKA:**Re-Ranking Algorithm, Output Reranking Algorithm.**Context:**- It can introduce information not available to the original ranking algorithm, such as a global predictor features.
- It can be:

**Example(s):**- MaxEnt-Rank (Charniak and Johnson, 2005; Ji and Grishman, 2005),
- SVMRank (Shen and Joshi, 2003),
- Voted Perceptron (Collins, 2002; Collins & Duffy, 2002; Shen & Joshi, 2004),
- Kernel Based Methods (Henderson and Titov, 2005),
- RankBoost (Collins, 2002; Collins & Koo, 2003; Kudo et al., 2005).

**See:**k-Best List Algorithm, Joint Inference Algorithm.

## References

### 2005

- (Collins & Koo, 2005) ⇒ Michael Collins, and Terry Koo. (2005). “Discriminative Reranking for Natural Language Parsing.” In: Computational Linguistics, 31(1) doi:10.1162/0891201053630273
- (Charniak & Johnson, 2005) ⇒ Eugene Charniak, and Mark Johnson. (2005). “Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking.” In: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics (ACL 2005) doi:10.3115/1219840.1219862

### 2001

- (Collins & Duffy, 2001) ⇒ Michael Collins, and Nigel Duffy. (2001). “Convolution Kernels for Natural Language.” In: Proceedings of NIPS 2001.