interestingness

英

美

网络  趣味性; 有趣的; 兴趣度; 有趣性; 兴趣性

英英释义

noun

• the power of attracting or holding one's attention (because it is unusual or exciting etc.)
  1. they said nothing of great interest
  2. primary colors can add interest to a room
  Synonym:interest

双语例句

• Lastly an algorithm of measuring interestingness of data mining schema based on user expectation and fuzzy logic is presented.
  最后对数据挖掘结果模式的价值进行了深入分析，利用模糊逻辑技术，在现有的兴趣度测量方式的基础上，介绍了一种新的模式兴趣度测量算法。
• The experiment shows that interestingness could reduce the number of rules while no interestingness could achieve optimal result for all data sets. Lastly, associative classification is used in electronical recommendation system.
  实验结果表明兴趣度可减少规则的数量但没有一个兴趣度对于所有数据集都能够达到最优的分类效果。最后，本文将关联分类应用于电子商务推荐系统中。
• The emerging of Sports TV not only increased interestingness and recreational use of television program, but also helped to disseminate sporting events.
  体育电视的出现，不仅为电视节目增加了趣味性和娱乐性，也为体育项目的传播起到推波助澜的作用。
• After introduction of some typical Web log preprocessing techniques, it is pointed out that the frame pages in a Web site can reduce the interestingness of the result page groups. Then, a frame-filtering algorithm is proposed to solve this problem.
  在介绍了典型的数据预处理技术的基础上，指出Frame页面降低了挖掘结果的兴趣性，并提出相应的解决方法&Frame页面过滤算法消除其影响。
• Improve students 'interestingness and learning efficiency by introduce examples like the impoundment of reservoir, the most value of resistors, sales pricing etc. that is familiar to students into the teaching and the aesthetic value of inequalities.
  学生熟悉的水库蓄水、电阻最值、销售定价等关于不等式的生活实例融入课堂教学及向同学们介绍相关不等式的美学价值等方式以达到提高数学教学的趣味性，提高学习效率。
• Associative and Correlative Regular Mining Based on Interestingness and PC-tree for Medical Images Data
  基于兴趣度和PC-树的医学图像数据关联且相关规则挖掘
• A m_d distance measure for evaluating the subject interestingness of data warehouse
  评估数据仓库主题兴趣度的Md距离测度方法
• After analyzing the quantitative association rules and interestingness of association rules which are encountered often in distributed association rule mining, the dissertation proposes the methods of changing the quantitative attributions into bool attributions using FCM and Gene algorithm.
  并且，在分析和研究了分布式关联规则挖掘中常见的数量型关联规则、关联规则的兴趣度问题的基础上提出了数量关联规则的聚类划分方法以及兴趣度过滤方法。
• In order to find the useful association rules, the interestingness of mining association rules is discussed.
  关联规则挖掘中的有趣性问题可从客观和主观两个方面对关联规则的兴趣度进行评测。
• The problem of discovering association rules consists of four elements: data set, the form of the rule, search algorithm, interestingness measure.
  关联规则发现问题可以归纳为四个要素：数据集、规则形式、搜索方法、兴趣度量。它们分别对应机器学习问题中的数据空间、假设空间、算法、评价标准。