Github repository: https://aldolipani.github.io/OwenShap
Github repository: https://aldolipani.github.io/sRBP
Github repository: https://aldolipani.github.io/ProbabilisticModels
Demo available: http://visualpool.aldolipani.com
Github repository: https://aldolipani.github.io/VisualPool/
With Pool bias in Information Retrieval (IR) is meant the bias of a test collection against new systems that appears as side-effect of the use of the pooling technique. In this repository we find the implementation of the pool bias estimators analyzed in the SIGIR-2015 paper: “Splitting Water: Precision and Anti-Precision to Reduce Pool Bias” and in the ECIR-2016 paper: “The Curious Incidence of Bias Corrections in the Pool”.
The application has two use cases, analysis of the test collection and run bias correction.
The available IR measures are: P@10, P@15, P@20, P@30 and P@100.
Source code and documentation available here.
Version of the application used to generate the results in the ECIR 2016 paper: "The Curious Incidence of Bias Corrections in the Pool".
Version of the application used to generate the results in the SIGIR 2015 paper: "Splitting Water: Precision and Anti-Precision to Reduce Pool Bias".