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Data Analysis and Knowledge Discovery  2019, Vol. 3 Issue (9): 77-87    DOI: 10.11925/infotech.2096-3467.2019.0301
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Cross-Language Information Retrieval Based on Weighted Association Patterns and Rule Consequent Expansion
Mingxuan Huang1,2,3(),Shoudong Lu3,Hui Xu3
1 Guangxi (ASEAN) Financial Research Center, Guangxi University of Finance and Economics, Nanning 530003, China
2 Guangxi Key Laboratory of Cross-border E-commerce Intelligent Information Processing, Guangxi University of Finance and Economics, Nanning 530003, China
3 School of Information and Statistics, Guangxi University of Finance and Economics, Nanning 530003, China
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Abstract  

[Objective] This paper proposes a new Cross-Language Information Retrieval (CLIR) model, aiming to address the issues facing natural language processing, such as query topic drift and word mismatch. [Methods] First, we explored the frequent item-sets with the weighted association patterns and the pruning strategies based on maximum i