Evaluating Information Retrieval Metrics Based on Bootstrap Hypothesis Tests
スポンサーリンク
概要
- 論文の詳細を見る
This paper describes how the bootstrap approach to statistics can be applied to the evaluation of IR effectiveness metrics. More specifically, we describe straightforward methods for comparing the discriminative power of IR metrics based on Bootstrap Hypothesis Tests. Unlike the somewhat ad hoc Swap Method proposed by Voorhees and Buckley, our Bootstrap Sensitivity Methods estimate the overall performance difference required to achieve a given confidence level directly from Bootstrap Hypothesis Test results. We demonstrate the usefulness of our methods using four different data sets (i.e., test collections and submitted runs) from the NTCIR CLIR track series for comparing seven IR metrics, including those that can handle graded relevance and those based on the Geometric Mean. We also show that the Bootstrap Sensitivity results are generally consistent with those based on the more ad hoc methods.
論文 | ランダム
- 保温折衷苗代用温床紙の再検討
- 共役リノレン酸含有油脂の酸化安定性に及ぼすトリアシルグリセロール分子種組成の影響
- Development of a Rapid Process Monitoring Method for Dry-Coated Tableting Process by Using Near-Infrared Spectroscopy
- Sterol Composition in Larvae of the Silkworm, Bombyx mori
- 大会シンポジウム 日本ロールシャッハ学会第5回大会シンポジウム 『自分のロールシャッハ』シンポジストほか発言要旨〔含 コメント〕