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  • Mining class-bridge rules based on rough sets 
    Zhang Shichao; Chen Qingfeng; Jin Zhi; Wang Ruili (Elsevier Science, 2009)
    A class-bridge rule is the rule whose antecedent and consequent belong to different conceptual classes. This kind of rules stands for the correlation between conceptual classes. The study on class-bridge rules can benefit ...
  • Mining Data Streams with Labeled and Unlabeled Training Examples 
    Zhang Peng; Zhu Xingquan; Guo Li (SIEEE Computer Society, 2009)
    In this paper, we propose a framework to build prediction models from data streams which contain both labeled and unlabeled examples. We argue that due to the increasing data collection ability but limited resources for ...
  • Mining dependent patterns in probabilistic databases 
    Zhang Shichao; Zhang Chengqi; Yu Jeffrey (Taylor and Francis, 2006)
  • Mining Domain Driven Correlations in Stock Markets 
    Lin Li; Luo Dan; Liu Li (Springer-Verlag, 2005)
    There have been many technical trading rules in stock market since the first stock exchange founded. Along with the developing of computer technology, the technical trading rules are playing more and more important roles ...
  • Mining Dynamic Databases by Weighting 
    Zhang Shichao; Liu Li (Dept of Informatics, University of Szeged, Hungary, 2003)
    A dynamic database is a set of transactions, in which the content and the size can change over time. There is an essential difference between dynamic database mining and traditional database mining. This is because recently ...
  • Mining Exceptional Activity Patterns in Microstructure Data 
    Ou Yuming; Cao Longbing; Luo Chao; Liu Li (IEEE Computer Society, 2008)
    Market Surveillance plays an important role in maintaining market integrity, transparency and fairnesss. The existing trading pattern analysis only focuses on interday data which discloses explicit and high-level market ...
  • Mining follow-up correlation patterns from time-related databases 
    Zhang Shichao; Huang Zifang; Zhang Jilian; Zhu Xiaofeng (Springer, 2008)
    Research on traditional association rules has gained a great attention during the past decade. Generally, an association rule A â¿¿ B is used to predict that B likely occurs when A occurs. This is a kind of strong correlation, ...
  • Mining for combined association rules on multiple datasets 
    Zhao Yanchang; Zhang Huaifeng; Figueiredo Fernando; Cao Longbing; Zhang Chengqi (Association for Computing Machinery, 2007)
  • Mining For The Antibody-antigen Interacting Associations That Predict The B Cell Epitopes 
    Zhao L; Li Jinyan (Biomed Central Ltd, 2010)
    Background: Predicting B-cell epitopes is very important for designing vaccines and drugs to fight against the infectious agents. However, due to the high complexity of this problem, previous prediction methods that focus ...
  • Mining frequent itemsets for protein kinase regulation 
    Chen Qingfeng; Chen Phoebe; Zhang Chengqi; Li Lianggang (Springer-Verlag, 2006)
    Protein kinases, a family of enzymes, have been viewed as an important signaling intermediary by living organisms for regulating critical biological processes such as memory. hormone response and cell growth. The unbalanced ...
  • Mining globally interesting patterns from multiple databases using kernel estimation 
    Zhang Shichao; You Xiaofang; Jin Zhi; Wu Xindong (Elsevier Science, 2009)
    When extracting knowledge (or patterns) from multiple databases, the data from different databases might be too large in volume to be merged into one database for centralized mining on one computer, the local information ...
  • Mining High Impact Exceptional Behavior Patterns 
    Cao Longbing; Zhao Yanchang; Figueiredo Fernando; Ou Yuming; Luo Dan (Springer-Verlag, 2007)
  • Mining impact-targeted activity patterns in imbalanced data 
    Cao Longbing; Zhao Yanchang; Zhang Chengqi (IEEE Computer Soc, 2008)
    Impact-targeted activities are rare but they may have a significant impact on the society. For example, isolated terrorism activities may lead to a disastrous event, threatening the national security. Similar issues can ...
  • Mining In Anticipation For Concept Change: Proactive-Reactive Prediction In Data Streams 
    Yang Y; Wu Xindong; Zhu Xingquan (Springer, 2006)
    Prediction in streaming data is an important activity in the modern society. Two major challenges posed by data streams are (1) the data may grow without limit so that it is difficult to retain a long history of raw data; ...
  • Mining in-depth patterns in stock market 
    Lin Li; Cao Longbing (Inderscience Publishers, 2008)
    Stock trading plays an important role for supporting profitable stock investment. In particular, more and more data mining-based technical trading rules have been developed and used in stock trading systems to assist ...
  • Mining interesting XML-enabled association rules with templates 
    Feng Ling; Dillon Tharam (Springer-Verlag Berlin, 2005)
    XML-enabled association rule framework [FDWC03] extends the notion of associated items to XML fragments to present associations among trees rather than simple-structured items of atomic values. They are more flexible and ...
  • Mining Iterative Generators And Representative Rules For Software Specification Discovery 
    Lo D; Li Jinyan; Wong Ls; Khoo Sc (IEEE Computer Soc, 2011)
    Billions of dollars are spent annually on software-related cost. It is estimated that up to 45 percent of software cost is due to the difficulty in understanding existing systems when performing maintenance tasks (i.e., ...
  • Mining key information of web pages 
    Lu Jie; Wang Changxin; Zhang Guangquan (Joint Conference On Information Sciences, 2005)
    Key information, in the form of distinctive menu items, navigation indicators provided by web site constructors, can classify the main contents of web pages and reflect certain taxonomy knowledge. Mining such information ...
  • Mining key information of web pages: a method and its application 
    Wang Chao; Lu Jie; Zhang Guangquan (Elsevier, 2001)
  • Mining Maximal Frequent Itemsets From Data Streams 
    Mao Gojun; Wu Xindong; Zhu Xingquan; Chen G; Liu Chunnian (Sage Publications Ltd, 2007)
    Frequent pattern mining from data streams is an active research topic in data mining. Existing research efforts often rely on a two-phase framework to discover frequent patterns: (1) using internal data structures to store ...