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interestingness

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 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。
  • 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。
  • 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
  • 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
  • Defining interestingness and putting forward new algorithm of mining association rules including negative items.
    定义兴趣度,提出挖掘含负属性项关联规则算法。
  • 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。
  • 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。
  • An Overview of Measures of Interestingness
    感兴趣度的研究综述
  • 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。
  • 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。