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 Interestingness Measure and its Application in Learning Guidance System
  兴趣度在选课指导系统中的研究与应用
• 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。
• A measure of Association Rule Interestingness
  关联规则兴趣度的度量
• 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。
• 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
• Mining Optimized Support and Interestingness Quantitative Association Rules
  挖掘支持度和兴趣度最优的数量关联规则
• 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。
• 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。
• As an important photoelectric exposure, field emission properties of III nitride semiconductors have attracted widely interestingness of researchers.
  而III族氮化物半导体场发射研究作为其光电特性的重要研究方向，引起了人们广泛关注。
• 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。