A learnable search result diversification method

作者：

Highlights：

• We introduce the learning mechanism to the query aspect diversification model.

• We utilize the Markov random field to integrate different types of features.

• We conduct extensive experiments to verify that our model achieves better performance.

摘要

•We introduce the learning mechanism to the query aspect diversification model.•We utilize the Markov random field to integrate different types of features.•We conduct extensive experiments to verify that our model achieves better performance.

论文关键词：Explicit search result diversification,Learning model,Markov random fields

论文评审过程：Received 25 June 2017, Revised 4 April 2018, Accepted 20 April 2018, Available online 24 April 2018, Version of Record 5 May 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.04.029