| Autor: |
Parambath, Shameem A Puthiya |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Proceedings of the 2022 ACM SIGIR International Conference on Theory of Information Retrieval |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1145/3539813.3545135 |
| Popis: |
We analyze different re-ranking algorithms for diversification and show that majority of them are based on maximizing submodular/modular functions from the class of parameterized concave/linear over modular functions. We study the optimality of such algorithms in terms of the `total curvature'. We also show that by adjusting the hyperparameter of the concave/linear composition to trade-off relevance and diversity, if any, one is in fact tuning the `total curvature' of the function for relevance-diversity trade-off. |
| Databáze: |
arXiv |
| Externí odkaz: |
|
