最近我们的工作重点在于利用人工智能技术对大数据进行深度的挖掘，开展多个领域的应用。
Recently, our work focuses on the use of artificial intelligence technology for large data mining depth, to carry out a number of areas of application.
IBM同时企盼类似的“云计算”能加速“大数据”时代的到来：即人们可以从海量的数字信息中挖掘出有用的知识。
It also anticipated that such cloud computing would accelerate the emergence of "big data" : huge piles of digital information that can be mined for valuable knowledge.
本文展示了使用Hadoop挖掘大数据的一个简单示例。
This article has shown you a simple example of crunching big data with Hadoop.
而多年在国外从事人工智能和大数据分析挖掘研究的肖京，对国内大数据应用更为看好。
And for many years engaged in artificial intelligence and big data analysis and Research on the excavation of Xiao Jing, the domestic big data applications more optimistic.
文本大数据分析与挖掘：机遇，挑战，及应用前景。
Analysis and Mining of Big Text Data: Opportunities, Challenges, and Applications.
该方法能通过并行投影和压缩技术扩展到大数据库中进行挖掘规则。
This method can be scaled up to very large databases by parallel projection and compress technique.
通过对大数据的挖掘、统计和分析，找到新的价值增长路线。
Through big data mining, statistic and analysis, find the new growth curve.
量化的安全度量技术在挖掘数据潜在的安全关系和处理大数据量方面比定性方法有明显优势。
The quantification of the security shows obvious superiority over the qualitative ways, especially when it is used to process large datasets and mine the security relations.
医学成像新技术、多模态医学成像的图像与信息融合、大数据病例的挖掘，是实现临床精准医疗的重要工程基础。
Precision Medicine relies on advent medical imaging technique, fusion of multi-modality medical imaging and information, and large-scale data mining on medical cases.
扩展了目前电信告警数据中的频繁情节挖掘算法，使之能够挖掘出具有两个时间界限的频繁情节规则，而且适合于大数据集挖掘。
We extend the current episodes rule discovery algorithm and make it be able to find episodes rule with two time bound and be applicable for large set database.
扩展后的DM 2平台具有极强的处理大数据集的能力，优异的与数据库交互的能力，人性化的可视化数据挖掘界面。
The expanded DM2 platform has extremely capacity to handle large data sets, excellent ability to interact with database and human visual interfaces of data mining.
除此之外，机器学习的理论方法还被用于大数据集的数据挖掘领域。
Additionally, machine learning methods are also applied to massive-sample data mining field.
除此之外，机器学习的理论方法还被用于大数据集的数据挖掘领域。
Additionally, machine learning methods are also applied to massive-sample data mining field.
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