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* update jdiq effectiveness commit sha * merge docs/jdiq2018-effectiveness.md to docs/experiments-jdiq2018.md
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### JDIQ2018 Effectiveness Scripts | ||
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The scripts calculate the optimal performances of all supported ranking models (by grid-searching all possible model parameters). | ||
The main purpose is to reproduce what we have in our JDIQ2018 paper: | ||
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_NOTICE: The query topics used in JDIQ paper are combined topics per collection while the numbers generated | ||
by the scripts here are separated_ | ||
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### Run | ||
On tuna: | ||
``` | ||
nohup python src/main/python/jdiq2018_effectiveness/run_batch.py --collection disk12 >& disk12.jdiq2018.log & | ||
nohup python src/main/python/jdiq2018_effectiveness/run_batch.py --collection robust04 >& robust04.jdiq2018.log & | ||
nohup python src/main/python/jdiq2018_effectiveness/run_batch.py --collection robust05 >& robust05.jdiq2018.log & | ||
nohup python src/main/python/jdiq2018_effectiveness/run_batch.py --collection wt10g >& wt10g.jdiq2018.log & | ||
nohup python src/main/python/jdiq2018_effectiveness/run_batch.py --collection gov2 >& gov2.jdiq2018.log & | ||
nohup python src/main/python/jdiq2018_effectiveness/run_batch.py --collection cw09b --metrics map ndcg20 err20 >& cw09b.jdiq2018.log & | ||
nohup python src/main/python/jdiq2018_effectiveness/run_batch.py --collection cw12b13 --metrics map ndcg20 err20 >& cw12b13.jdiq2018.log & | ||
``` | ||
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### Results | ||
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${results} |
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