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

• 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。
• 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
• 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。
• 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。
• 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
• 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。
• WWW Personalized Information Retrieval Based on Measures of Interestingness
  基于感兴趣度的WWW个性化信息发现
• It uses interestingness threshold to filter rules in order to reduce the number of association rules, which are useless, inappropriate.
  兴趣度模型采用兴趣度参数对规则进行筛选，减少关联规则的个数，去掉一些无用、不合适的规则。