Browsing by Author "Qin Zhenxing"

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Browsing by Author "Qin Zhenxing"

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  • Association -based Segmentation for Chinese-crossed Query Expansion 
    Zhang Chengqi; Qin Zhenxing; Yan Xiaowei (IEEE Computer Society, 2005)
    The continually and high-rate growth of China's economy has attracted more and more international investors. These investors have an urgent need of identifying patterns in Chinese information, which are potentially ...
  • Clinical Patterns of Obstructive Sleep Apnea and Its Comorbid Conditions: A Data Mining Approach 
    Huang Qi Rong; Qin Zhenxing; Zhang Shichao; Chow Chin (The American Academy of Sleep Medicine, 2008)
    Objectives: Obstructive sleep apnea often results in a wide range of comorbid conditions. Although some conditions have been clearly identified as comorbid, a full clinical pattern of associated diseases has not been ...
  • Cost Sensitive Classification in Data Mining 
    Qin Zhenxing; Zhang Chengqi; Wang Tao; Zhang Shichao (Springer-Verlag, 2010)
    Cost-sensitive classification is one of mainstream research topics in data mining and machine learning that induces models from data with unbalance class distributions and impacts by quantifying and tackling the unbalance. ...
  • Cost-Sensitive Decision Trees with Multiple Cost Scales 
    Qin Zhenxing; Zhang Shichao; Zhang Chengqi (Springer-Verlag, 2004)
    How to minimize misclassification errors has been the main focus of Inductive learning techniques, such as CART and C4.5. However, misclassification error is not the only error in classification problem. Recently, ...
  • Cost-sensitive Semi-supervised Classification using CS-EM 
    Qin Zhenxing; Zhang Shichao; Liu Li; Wang Tao (IEEE Computer Society, 2008)
    In many real world data mining and classification tasks, we face with the problem of high cost in making training data sets. In addition, in many domains, different misclassification errors involve different costs. These ...
  • Dynamic test-sensitive decision trees with multiple cost scales 
    Qin Zhenxing; Zhang Chengqi; Xie Xuehui; Zhang Shichao (Springer-Verlag, 2006)
  • Handling over-fitting in test cost-sensitive decision tree learning by feature selection, smoothing and pruning 
    Wang Tao; Qin Zhenxing; Jin Zhi; Zhang Shichao (Elsevier Ltd, 2010)
    Cost-sensitive learning algorithms are typically designed for minimizing the total cost when multiple costs are taken into account. Like other learning algorithms, cost-sensitive learning algorithms must face a significant ...
  • Identification Of Important Factors For Water Vapor Flux And Co2 Exchange In A Cropland 
    Qin Zhenxing; Su Gao-Li; Zhang Ji-Wen; Ouyang Ying; Yu Qiang; Li Jianchun (Elsevier Science Bv, 2010)
    Water vapor flux and carbon dioxide (CO2) exchange in croplands are crucial to water and carbon cycle research as well as to global warming evaluation. In this study, a standard three-layer feed-forward back propagation ...
  • Identifying exceptional patterns in multi-databases 
    Zhang Chengqi; Zhang Shichao; Yan Xiaowei; Qin Zhenxing (Nanyang Technological University, 2002)
    Many interstate organizations have a pressing need to analyze their data in multi-databases, distributed throughout their branches. Traditional multi-database mining still utilize mono-database mining techniques. This ...
  • Incorporating medical history to cost sensitive classification with lazy learning strategy 
    Qin Zhenxing; Wang Tao; Zhang Shichao (IEEE, 2010)
    This paper studies an actual and new setting of cost-sensitive learning, i.e., combining test data with medical history under multiple-scale cost constraints. With a new cost structure, an attribute selection strategy is ...
  • Indexing by Conditional Association Semantics 
    Yan Xiaowei; Zhang Chengqi; Zhang Shichao; Qin Zhenxing (Idea Group Publishing, 2003)
    Prevailing information retrieval methods are based on either term similarity or latent semantics. Terms are considered independently. This paper presents a new strategy for information retrieval, i.e., indexing by conditional ...
  • Mind the Trends when you Mine: Incremental Data Mining 
    Zhang Chengqi; Zhang Shichao; Yan Xiaowei; Qin Zhenxing (Nanyang Technological University, 2002)
    This paper presents a new mining model for identifying both frequent itemsets and trend patterns. This method uses weighting techniques to increase efficiency, enabling us to reuse frequent itemsets mined previously. ...
  • Mining Term Association Rules for Heuristic Query Construction 
    Qin Zhenxing; Liu Li; Zhang Shichao (Springer-Verlag, 2004)
    As the Web has become an important channel of information floods, users have had difficulty on identifying what they really want from huge amounts of rubbish-like information provided by the Web search engines when utilizing ...
  • Missing is useful: Missing values in cost-sensitive decision trees 
    Qin Zhenxing; Ling Charles; Zhang Shichao; Sheng Shengli (Institute of Electrical and Electronics Engineers, 2005)
    Many real-world data sets for machine learning and data mining contain missing values and much previous research regards it as a problem and attempts to impute missing values before training and testing. In this paper, ...
  • Missing or absent? A question in Cost-sensitive Decision Tree 
    Qin Zhenxing; Zhang Shichao; Zhang Chengqi (IOS Press, 2006)
  • Modeling Temporal Semantics of Data 
    Zhang Shichao; Zhang Chengqi; Qin Zhenxing (Grace Publications, 2003)
    Recently, many temporal query languages, such as TCAL and TQuel have been proposed for temporal databases. However, there are still some limitations such as the inadequacy on operating data with temporal elements and ...
  • Preprocessing Time Series Data for Classification with Application to CRM 
    Yang Yiming; Yang Qiang; Lu Wei; Pan Jialin; Pan Rong; Lu Chenhui; Li Lei; Qin Zhenxing (Springer-Verlag, 2005)
    We develop an innovative data preprocessing algorithm for classifying customers using unbalanced time series data. This problem is directly motivated by an application whose aim is to uncover the customers' churning ...