Modeling Document Novelty with Neural Tensor Network for Search Result Diversification

Training data

• feature.txt and feature_test.txt: document/query featture vectors
• idealfile: groundtruth ranking for each query

Command line

python DiverseNTN.py feature.txt feature_test.txt idealfile config.yml

Results

The training results are saved in fold reslut

Reference

[1] Long Xia, Jun Xu, Yanyan Lan, Jiafeng Guo, Xueqi Cheng. Modeling Document Novelty with Neural Tensor Network for Search Result Diversification. In Proc. SIGIR 2016.