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

• The Comparative Study on Interestingness Measures for Mining Association Rules
  关联规则兴趣度度量方法的比较研究
• For objective measure the interestingness of association rules is first defined on the basis of the support and confidence of association rules and the interestingness of association rules is then eval-uated accordingly.
  在关联规则的置信度和支持度基础上对关联规则的有趣性的客观评测增加了约束。
• On the other hand, the ironic language enhances the readability, interestingness and perceptibility of the novel, and provides a fresh aesthetic pleasure to the reader.
  另一方面，反讽式的语言增强了小说的趣味性和可读性，提高了小说的可感性，并使读者获得新的审美愉悦。
• 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。
• 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。
• At the same time, the users 'interested changes are tracked dynamically according to the reading actions, and the interesting ontological profile is submitted, then the measure of interestingness is analyzed and calculated.
  再借助精细语义逐句解读其内容，提取用户所关注的信息.根据用户的阅读行为动态了解用户的兴趣变化，建立用户兴趣的本体模型，并分析和定义了用户兴趣度的度量。
• WWW Personalized Information Retrieval Based on Measures of Interestingness
  基于感兴趣度的WWW个性化信息发现
• Interestingness Research of Association Rules in Incremental Mining Data
  兴趣度在增量的关联规则挖掘中的研究
• In this paper, some common interestingness are introduced and an experiment compares the classification impact of different interestingness on different data sets.
  本文对目前比较常见的兴趣度进行了总结，并通过实验比较了不同兴趣度对于不同数据集的分类效果。
• 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。