Cross-language Information Retrieval Based on Multiple Information

被引：1

作者：

Liu, Pengyuan ^{[1
]}

Zheng, Zhijun ^{[1
]}

Su, Qi ^{[2
]}

机构：

[1] Beijing Language & Culture Univ, Sch Informat Sci, Beijing, Peoples R China

[2] Peking Univ, Sch Foreign Languages, Beijing, Peoples R China

来源：

2018 IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE (WI 2018) | 2018年

关键词：

Cross-language information retrieval; Multi information Integration; Parallel CNN;

D O I：

10.1109/WI.2018.00-26

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

As predicted by Internet Data Center (IDC), the amount of global language data will exceed 40ZB by 2020. With the globalization of information, it has become an urgent matter for current web retrieval to break the barriers between languages. In this paper, we propose to integrate semantic and lexical information to deal with the task of cross language information retrieval (CLIR). The approach does not rely on external knowledge bases thus to avoid that knowledge bases cannot deal with net neologism. Experiments on Sogou dataset show the feasibility of the approach.

引用

页码：623 / 626

页数：4

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