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.
LIANG Ye (梁野)
. Multilingual Financial News Retrieval and Smart Recommendation Based on Big Data[J]. Journal of Shanghai Jiaotong University(Science), 2016
, 21(1)
: 18
-24
.
DOI: 10.1007/s12204-016-1694-3
[1] GERSH J R, BOS N. Cognitive and organizationalchallenges of big data in cyber defense[C]//Proceedings of the 1st Workshop on Human-Centered Big Data Research. Raleigh, RC, USA: ACM,2014: 4-8.
[2] CUZZOCREA A. Privacy and security of big data:Current challenges and future research perspectives[C]//Proceedings of the First International Workshopon Privacy and Secuirty of Big Data. Shanghai, China:ACM, 2014: 45-47.
[3] BONIFATI A, CIUCANU R, LEMAY A, etal. A paradigm for learning queries on big data[C]//Proceedings of the First International Workshopon Bringing the Value of Big Data to Users. Hangzhou,China: ACM, 2014: 7-12.
[4] NAYAK R, SENELLART P, SUCHANEK F M, etal. Discovering interesting information with advancesin web technology [J]. SIGKDD Explorations Newsletter,2013, 14(2): 63-81.
[5] KUMAR B A. Profound survey on cross language informationretrieval methods (CLIR) [C]//Proceedingsof the 2nd International Conference on Advanced Computing& Communication Technologies. [s. l.]: IEEE,2012: 64-68.
[6] LIU Y, TIAN M, ZHOU W T, et al. A cross languagetext categorization algorithm from the perspectiveof information retrieval [C]//Proceedings of theIndustrial Control and Electronics Engineering. [s. l.]:IEEE, 2012: 254-257.
[7] ZHU W H, LUO L H, JU C Y, et al. Cross languageinformation extraction for digitized textbooksof specific domains [C]//Proceedings of the Computerand Information Technology. [s. l.]: IEEE, 2012: 1114-1118.
[8] MENG X F, CI X. Big data management: Concepts,techniques and challenge [J]. Journal of Computer Researchand Development, 2013, 50(1): 146-169 (in Chinese).
[9] QIN X P, WANG H J, LI F R, et al. New landscapeof data management technologies [J]. Journal of Software,2013, 24(2): 175-197 (in Chinese).
[10] LIU T T, LI C, HU Q C, et al. Multiple-replicas managementin the cloud environment [J]. Journal of ComputerResearch and Development, 2011, 48(Sup.): 254-260 (in Chinese).
