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Overview of cross-language retrieval technology based on knowledge graph

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DOI: 10.23977/icasit.2019.029


Shengyin Zhu, Xiangzhen He, Honzhi Yu

Corresponding Author

Xiangzhen He


The “sootc” e-commerce platform of One Belt and One Road provides users with a clearer, more intuitive and comprehensive information retrieval after the introduction of knowledge graph. Besides, it not only implements semantic retrieval, but also provides a better retrieval experience in terms of user personalized recommendation and scene-based real-time information service. With the ideas and methods of multi-language knowledge graph, the authors have carried out experiments and analyze the construction of semantic search functions of Chinese, Tibetan, Mongolian, English and other cross-language systems. Through the analysis of data, we take regions as the mapping entity, and realize the structure of "entity--- relationship--- entity". Each language is an entity, and entities are corresponding. Each language entity takes the triple of "entity ---attribute--- value" as the basic expression of fact. Then all stored data constitute a huge multi-language entity relationship network of commodity information, forming a multi-language knowledge graph of commodity information.


Knowledge graph, cross-language retrieval, multi-language

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