Search Result Diversification

Learning to Diversify Search Result via Subtopic Attention

Zhengbao Jiang, rucjzb*AT*163*dot*com
Zhicheng Dou, dou*AT*ruc*dot*edu*dot*cn
Renmin University of China


This page provides the data and the code of the Document Sequence with Subtopic Attention (DSSA) model proposed in this paper:

                  author = {Jiang, Zhengbao and Wen, Ji-Rong and Dou, Zhicheng and Zhao, Wayne Xin and Nie, Jian-Yun and Yue, Ming},
                  title = {Learning to Diversify Search Results via Subtopic Attention},
                  booktitle = {Proceedings of the 40th SIGIR},
                  year = {2017},


Please download the paper and the slides


The data required to reproduce the experimental results can be downloaded from data_cv.tar.gz. This compressed file encompasses training and testing samples, relevance features, and embeddings of documents and queries.


The code and usage are available at The README file clearly illustrates how to run the code to reproduce the experimental results. It also explains the format of the input files and some implementation details.