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

• 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
• 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 measure of Association Rule Interestingness
  关联规则兴趣度的度量
• At the same time, a new objective interestingness function, which can measure the novelty and simplicity of linguistic value association rules, is given to reduce workload of selecting the interesting linguistic value association rules.
  同时，给出一个能够度量语言值关联规则简洁性和新奇性的客观关注程度（兴趣度）的计算函数，用于减少选取关注语言值关联规则的工作量。
• 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。
• Those of us who tell ourselves we are curious about the world are actually swimming in evidence that has been filtered again and again in favour of interestingness.
  我们当中那些告诉自己我对世界充满好奇的人，其实是遨游在证据的海洋中，而这些证据早已经过一次又一次过滤，使其有意思。
• WWW Personalized Information Retrieval Based on Measures of Interestingness
  基于感兴趣度的WWW个性化信息发现
• 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。
• 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。