共检索到62条结果
全部
订阅
收起
  • [外文会议] Yanqing Zhu William Zhu 2014
    As one of three basic theories of granular computing, rough set theory provides a useful tool for dealing with the granularity in information systems. Covering-based rough set theory is a generalizatio...
    CoveringRough setGranular computingApproximation operatorSet-valued information system
  • [外文会议] Bin Yang William Zhu 2014
    As a technique for granular computing, rough sets deal with the vagueness and granularity in information systems. Covering-based rough sets are natural extensions of the classical rough sets by relaxin...
    Granular computingCoveringRough setNeighborhoodInclusion degreeNetwork security
  • [外文会议] Junxia Niu Hong Zhao William Zhu 2014
    Minimal test cost attribute reduction is an important problem in cost-sensitive learning since it reduces the dimensionality of the attributes space. To address this issue, many heuristic algorithms ha...
    Cost-sensitive learningGranular computingAttribute reductionTest costLogarithmic weighted algorithm
  • [外文会议] Anjing Fan Hong Zhao William Zhu 2014
    The minimal test cost attribute reduction is an important component in data mining applications, and plays a key role in cost-sensitive learning. Recently, several algorithms are proposed to address th...
    Cost-sensitive learningMinimal test costAttribute reductionGranular computingBiologically-inspired algorithm
  • [外文会议] Xu He Fan Min William Zhu 2014
    Recommender systems are popular in e-commerce as they provide users with items of interest. Existing top-K approaches mine the K strongest granular association rules for each user, and then recommend r...
    Granular computingRecommender systemGranule association rulesConfidenceSignificance
  • [外文会议] Bingxin Xu Huiping Chen William Zhu Xiaozhong Zhu 2013
    Cost-sensitive learning is both hot and difficult in data mining and machine learning applications. Some research considers only one type of cost. Others convert two or more types of cost into the same...
    Cost-sensitive learningrough setsattribute reductionmoney costtime cost
  • [外文会议] Fan Min William Zhu 2013
    Recommender systems are important for e-commerce companies as well as researchers. Recently, granular association rules have been proposed for cold-start recommendation. However, existing approaches re...
    Granular computingrecommender systemgranule association rulecoverageconfidence
  • [外文会议] Xu He Fan Min William Zhu 2013
    Granular association rule mining is a new relational data mining approach to reveal patterns hidden in multiple tables. The current research of granular association rule mining considers only nominal d...
    Granular association rule miningDiscretizationEqual WidthEqual FrequencyRelational data mining
  • [外文会议] Fan Min William Zhu 2013
    Granular association rule is a new approach to reveal patterns hide in many-to-many relationships of relational databases. Different types of data such as nominal, numeric and multi-valued ones should ...
    Association ruleRecommender systemMulti-valuePositive granuleNegative granule
  • [外文会议] Bin Yang William Zhu 2013
    Rough set theory is an effective tool for dealing with vagueness or uncertainty in information systems. It is efficient for data pre-process and widely used in attribute reduction in data mining. Matro...
    Generalized rough setsMatroidCircuitUnion of matroidsUpper and lower approximations
回到顶部
选择了条数据