rmit-ir/joint-cascade-ranking

Joint Optimization of Cascade Ranking Models (WSDM 19)

Joint Optimization of Cascade Ranking Models

Implementation of the cascade models used in the paper Joint Optimization of Cascade Ranking Models, WSDM 19.

L. Gallagher and R-C. Chen and R. Blanco and J. S. Culpepper. 2019. Joint Optimization of Cascade Ranking Models. In Proc. WSDM. 15-23. DOI: https://doi.org/10.1145/3289600.3290986

Reproduce Instructions

1. Make sure you have installed the dependencies:

   • g++ or clang++
   • cmake 2.8+
   • Python 3.3+
   • MSLR-WEB10K
   • Yahoo LTR Set 1

2. Clone the repo:

   $ git clone https://github.com/rmit-ir/joint-cascade-ranking
   $ cd joint-cascade-ranking
   $ git submodule update --init --recursive

3. Build/Install Dependencies

   Build CEGB (note CEGB was added to LightGBM core after the publication of this work):

   $ cd ext/cegb
   $ mkdir build
   $ cd build
   $ cmake ..
   $ make
   $ cd ../../..

   Build evaluation tools:

   $ make -C eval

   Install Python dependencies:

   $ pip install -r requirements.txt
   $ pip install -e ext/cegb/python-package

4. Configure Datasets

   Create a local.mk file with the path to MSLR and Yahoo datasets:

   $ >local.mk
   $ echo "YAHOO_PATH=/path/to/yahoo" >> local.mk
   $ echo "MSLR_PATH=/path/to/mslr" >> local.mk

   Link to datasets and create qrels:

   $ make -C exp/yahoo
   $ make -C exp/mslr

5. Run baselines

   Yahoo:

   $ ./exp/yahoo/baseline-gbrt.sh
   $ ./exp/yahoo/baseline-cegb.sh

   MSLR:

   $ ./exp/mslr/baseline-gbrt.sh
   $ ./exp/mslr/baseline-cegb.sh

6. Run joint cascade

   $ ./exp/yahoo/reproduce.sh
   $ ./exp/mslr/reproduce.sh