Cross-Language Information Retrieval Based on Multiple Information

Pengyuan Liu, Zhijun Zheng, Qi Su
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引用次数: 1

Abstract

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.
基于多信息的跨语言信息检索
据互联网数据中心(IDC)预测,到2020年,全球语言数据量将超过40ZB。随着信息的全球化,打破语言间的障碍已成为当前网络检索的当务之急。本文提出将语义信息与词汇信息相结合的方法来处理跨语言信息检索任务。该方法不依赖于外部知识库,避免了知识库无法处理网络新词的问题。在搜狗数据集上的实验证明了该方法的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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