Journal of shanghai Jiaotong University (Science) ›› 2016, Vol. 21 ›› Issue (1): 18-24.doi: 10.1007/s12204-016-1694-3

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Multilingual Financial News Retrieval and Smart Recommendation Based on Big Data

Multilingual Financial News Retrieval and Smart Recommendation Based on Big Data

LIANG Ye (梁野)   

  1. (Department of Computer Science, Beijing Foreign Studies University, Beijing 100089, China)
  2. (Department of Computer Science, Beijing Foreign Studies University, Beijing 100089, China)
  • Online:2016-02-29 Published:2016-03-21
  • Contact: LIANG Ye (梁野)

Abstract: In view of the study of finance and economics information, we research on the real-time financial news posted on the authority sites in the world’s major advanced economies. Analyzing the massive financial news of different information sources and language origins, we come up with a basic theory model and its algorithm on financial news, which is capable of intelligent collection, quick access, deduplication, correction and integration with financial news’ backgrounds. Furthermore, we can find out connections between financial news and readers’ interest. So we can achieve a real-time and on-demand financial news feed, as well as provide a theoretical basis and verification of the scientific problems on real-time processing of massive information. Finally, the simulation experiment shows that the multilingual financial news matching technology can give more help to distinguish the similar financial news in different languages than the traditional method.

Key words: financial news big data| multilingual| financial news retrieval| smart recommendation

摘要: In view of the study of finance and economics information, we research on the real-time financial news posted on the authority sites in the world’s major advanced economies. Analyzing the massive financial news of different information sources and language origins, we come up with a basic theory model and its algorithm on financial news, which is capable of intelligent collection, quick access, deduplication, correction and integration with financial news’ backgrounds. Furthermore, we can find out connections between financial news and readers’ interest. So we can achieve a real-time and on-demand financial news feed, as well as provide a theoretical basis and verification of the scientific problems on real-time processing of massive information. Finally, the simulation experiment shows that the multilingual financial news matching technology can give more help to distinguish the similar financial news in different languages than the traditional method.

关键词: financial news big data| multilingual| financial news retrieval| smart recommendation

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