Journal Papers

Xu, Kan

Lin, HF; Lin, Y (reprint author), Dalian Univ Technol, Dalian, Peoples R China.

Feng, Jiaojiao,Wang, Kaiqiao,Lin, Hongfei,Lin, Yuan

2019-01-01

JOURNAL OF NONLINEAR AND CONVEX ANALYSIS

SCIE

J

20

6,SI

1233-1240

1345-4773

Learning to rank; query expansion; patent retrieval; LambdaMART; semantic dictionary

The query expansion can select expanded words to add to the original query based on semantic relationships and terms co-occurrence relationships to better understand the user's query intent. This paper proposes a method of using semantic dictionary WordNet as an external resource for query expansion to improve patent retrieval. LambdaMART method was used to be combined with different query expansion to improve the performance of patent retrieval. Experiments on TREC datasets showed that the learning to rank model, which used WordNet to modify expanded term weights, has better performance and improves the performance of patent retrieval.