01437nas a2200229 4500008004100000245007000041210006900111260001200180300001300192490000700205520075300212653002700965653003900992653002101031653002801052100001901080700001701099700001501116700001801131700001801149856004001167 2010 eng d00aPattern Space Maintenance for Data Updates and Interactive Mining0 aPattern Space Maintenance for Data Updates and Interactive Minin c08/2010 a 282-3170 v263 aThis paper addresses the incremental and decremental maintenance of the frequent pattern space. We conduct an in-depth investigation on how the frequent pattern space evolves under both incremental and decremental updates. Based on the evolution analysis, a new data structure, Generator-Enumeration Tree (GE-tree), is developed to facilitate the maintenance of the frequent pattern space. With the concept of GE-tree, we propose two novel algorithms, Pattern Space Maintainer+ (PSM+) and Pattern Space Maintainer- (PSM-), for the incremental and decremental maintenance of frequent patterns. Experimental results demonstrate that the proposed algorithms, on average, outperform the representative state-of-the-art methods by an order of magnitude.10aData mining algorithms10adata update and interactive mining10afrequent pattern10aincremental maintenance1 aFeng, Mengling1 aDong, Guozhu1 aLi, Jinyan1 aTan, Yap-Peng1 aWong, Limsoon uhttp://knoesis.wright.edu/node/163801234nas a2200133 4500008004100000245004700041210004600088520085700134100001500991700001801006700001901024700001701043856004001060 2009 eng d00aMaintenance of Frequent Patterns: A Survey0 aMaintenance of Frequent Patterns A Survey3 aThis chapter surveys the maintenance of frequent patterns in transaction datasets. It is written to be accessible to researchers familiar with the field of frequent pattern mining. The frequent pattern main-tenance problem is summarized with a study on how the space of frequent patterns evolves in response to data updates. This chapter focuses on incremental and decremental maintenance. Four major types of maintenance algorithms are studied: Apriori-based, partition-based, prefix-tree-based, and concise-representation-based algorithms. The authors study the advantages and limitations of these algorithms from both the theoretical and experimental perspectives. Possible solutions to certain limitations are also proposed. In addition, some potential research opportunities and emerging trends in frequent pat-tern maintenance are also discussed.1 aLi, Jinyan1 aWong, Limsoon1 aFeng, Mengling1 aDong, Guozhu uhttp://knoesis.wright.edu/node/205702170nas a2200133 4500008004100000245004100041210004100082520180700123100001701930700001601947700001801963700001501981856004001996 2009 eng d00aMining Conditional Contrast Patterns0 aMining Conditional Contrast Patterns3 aThis chapter considers the problem of 'conditional contrast pattern mining.' It is related to contrast mining, where one considers the mining of patterns/models that contrast two or more datasets, classes, conditions, time periods, and so forth. Roughly speaking, conditional contrasts capture situations where a small change in patterns is associated with a big change in the matching data of the patterns. More precisely, a conditional contrast is a triple (B, F_{1}, F_{2}) of three patterns; B is the condition/context pattern of the conditional contrast, and F_{1} and F_{2} are the contrasting factors of the conditional contrast. Such a conditional contrast is of interest if the difference between F_{1} and F_{2} as itemsets is relatively small, and the difference between the corresponding matching dataset of B∪F_{1} and that of B∪F_{2 is relatively large. It offers insights on 'discriminating' patterns for a given condition B. Conditional contrast mining is related to frequent pattern mining and analysis in general, and to the mining and analysis of closed pattern and minimal generators in particular. It can also be viewed as a new direction for the analysis (and mining) of frequent patterns. After formalizing the concepts of conditional contrast, the chapter will provide some theoretical results on conditional contrast mining. These results (i) relate conditional contrasts with closed patterns and their minimal generators, (ii) provide a concise representation for conditional contrasts, and (iii) establish a so-called dominance-beam property. An efficient algorithm will be proposed based on these results, and experiment results will be reported. Related works will also be discussed.1 aDong, Guozhu1 aLiu, Guimei1 aWong, Limsoon1 aLi, Jinyan uhttp://knoesis.wright.edu/node/205800479nas a2200133 4500008004100000245010800041210006900149100001500218700001800233700001800251700001900269700001700288856004000305 2007 eng d00aEvolution and Maintenance of Frequent Pattern Space When Transactions Are Removed. Proceedings of PAKDD0 aEvolution and Maintenance of Frequent Pattern Space When Transac1 aLi, Jinyan1 aWong, Limsoon1 aTan, Yap-Peng1 aFeng, Mengling1 aDong, Guozhu uhttp://knoesis.wright.edu/node/111500452nas a2200133 4500008004100000245009300041210006900134100001800203700001500221700001700236700001100253700001400264856004000278 2006 eng d00aMinimum Description Length (MDL) Principle: Generators Are Preferable to Closed Patterns0 aMinimum Description Length MDL Principle Generators Are Preferab1 aWong, Limsoon1 aLi, Jinyan1 aDong, Guozhu1 aLi, H.1 aPei, Jian uhttp://knoesis.wright.edu/node/110500415nas a2200121 4500008004100000245006800041210006600109100001800175700002800193700001500221700001700236856004000253 2004 eng d00aDeEPs: A New Instance-based Discovery and Classification System0 aDeEPs A New Instancebased Discovery and Classification System1 aWong, Limsoon1 aRamamohanarao, Kotagiri1 aLi, Jinyan1 aDong, Guozhu uhttp://knoesis.wright.edu/node/149700343nas a2200109 4500008004100000245004900041210004900090100001900139700001800158700001700176856004000193 2003 eng d00aIncremental Recomputation in Local Languages0 aIncremental Recomputation in Local Languages1 aLibkin, Leonid1 aWong, Limsoon1 aDong, Guozhu uhttp://knoesis.wright.edu/node/148100325nas a2200109 4500008004100000245004000041210004000081100001700121700001800138700001900156856004000175 2000 eng d00aLocal Properties of Query Languages0 aLocal Properties of Query Languages1 aDong, Guozhu1 aWong, Limsoon1 aLibkin, Leonid uhttp://knoesis.wright.edu/node/154200387nas a2200121 4500008004100000245005800041210005700099100001800156700001700174700001900191700001500210856004000225 1999 eng d00aCAEP: Classification by Aggregating Emerging Patterns0 aCAEP Classification by Aggregating Emerging Patterns1 aWong, Limsoon1 aDong, Guozhu1 aZhang, Xiuzhen1 aLi, Jinyan uhttp://knoesis.wright.edu/node/153200377nas a2200121 4500008004100000245005200041210005200093100001900145700001600164700001700180700001800197856004000215 1999 eng d00aMaintaining Transitive Closure of Graphs in SQL0 aMaintaining Transitive Closure of Graphs in SQL1 aLibkin, Leonid1 aSu, Jianwen1 aDong, Guozhu1 aWong, Limsoon uhttp://knoesis.wright.edu/node/153400396nas a2200109 4500008004100000245008200041210006900123100001900192700001800211700001700229856004000246 1999 eng d00aUsing CAEP to Predict Translation Initiation Sites from Genomic DNA Sequences0 aUsing CAEP to Predict Translation Initiation Sites from Genomic 1 aZhang, Xiuzhen1 aWong, Limsoon1 aDong, Guozhu uhttp://knoesis.wright.edu/node/153300403nas a2200121 4500008004100000245006200041210006200103100002200165700001900187700001700206700001800223856004000241 1998 eng d00aRelational expressive power of constraint query languages0 aRelational expressive power of constraint query languages1 aBenedikt, Michael1 aLibkin, Leonid1 aDong, Guozhu1 aWong, Limsoon uhttp://knoesis.wright.edu/node/151700325nas a2200109 4500008004100000245004000041210004000081100001800121700001900139700001700158856004000175 1997 eng d00aLocal properties of query languages0 aLocal properties of query languages1 aWong, Limsoon1 aLibkin, Leonid1 aDong, Guozhu uhttp://knoesis.wright.edu/node/151100352nas a2200097 4500008004100000245006900041210006900110100001700179700001800196856004000214 1997 eng d00aSome Relationships between FOIES and Sigma 1 1 Arity Hierarchies0 aSome Relationships between FOIES and Sigma 1 1 Arity Hierarchies1 aDong, Guozhu1 aWong, Limsoon uhttp://knoesis.wright.edu/node/150601862nas a2200145 4500008004100000245006200041210006200103300000900165520142600174100002201600700001701622700001901639700001801658856004001676 1996 eng d00aRelational Expressive Power of Constraint Query Languages0 aRelational Expressive Power of Constraint Query Languages a5-163 aThe expressive power of first-order query languages with several classes of equality and inequality constraints is studied in this paper. We settle the conjecture that recursive queries such as parity test and transitive closure cannot be expressed in the relational calculus augmented with polynomial inequality constraints over the reals. Furthermore, noting that relational queries exhibit several forms of genericity, we establish a number of collapse results of the following form: The class of generic boolean queries expressible in the relational calculus augmented with a given class of constraints coincides with the class of queries expressible in the relational calculus (with or without an order relation). We prove such results for both the natural and active-domain semantics. As a consequence, the relational calculus augmented with polynomial inequalities expresses the same classes of generic boolean queries under both the natural and active-domain semantics. In the course of proving these results for the active-domain semantics, we establish Ramsey-type theorems saying that any query involving certain kinds of constraints coincides with a constraint free query on databases whose elements come from a certain innite subset of the domain. To prove the collapse results for the natural semantics, we make use of techniques from nonstandard analysis and from the model theory of ordered structures.
1 aBenedikt, Michael1 aDong, Guozhu1 aLibkin, Leonid1 aWong, Limsoon uhttp://knoesis.wright.edu/node/150800491nas a2200121 4500008004100000245010100041210006900142260006400211100001700275700001900292700001800311856004000329 1995 eng d00aOn impossibility of decremental recomputation of recursive queries in relational calculus and SQ0 aimpossibility of decremental recomputation of recursive queries bFifth International Database Programming Languages Workshop1 aDong, Guozhu1 aLibkin, Leonid1 aWong, Limsoon uhttp://knoesis.wright.edu/node/1817}