It is nontrivial to maintain such discovered frequent query patterns in real XML-DBMS because the transaction database of queries may allow frequent updates and such updates may not only invalidate some existing frequ...It is nontrivial to maintain such discovered frequent query patterns in real XML-DBMS because the transaction database of queries may allow frequent updates and such updates may not only invalidate some existing frequent query patterns but also generate some new frequent query patterns. In this paper, two incremental updating algorithms, FUX-QMiner and FUXQMiner, are proposed for efficient maintenance of discovered frequent query patterns and generation the new frequent query patterns when new XMI, queries are added into the database. Experimental results from our implementation show that the proposed algorithms have good performance. Key words XML - frequent query pattern - incremental algorithm - data mining CLC number TP 311 Foudation item: Supported by the Youthful Foundation for Scientific Research of University of Shanghai for Science and TechnologyBiography: PENG Dun-lu (1974-), male, Associate professor, Ph.D, research direction: data mining, Web service and its application, peerto-peer computing.展开更多
This paper addresses the mathematical relation on a set of periods and temporal indexing construc- tions as well as their applications.First we introduce two concepts, i.e.the temporal connection and temporal inclusio...This paper addresses the mathematical relation on a set of periods and temporal indexing construc- tions as well as their applications.First we introduce two concepts, i.e.the temporal connection and temporal inclusion, which are equivalence relation and preorder relation respectively.Second, by study- ing some basic topics such as the division of ＂large＂ equivalence classes and the overlaps of preorder relational sets, we propose a temporal data index model （TDIM） with a tree-structure consisting of a root node, equivalence class nodes and linearly ordered branch nodes.Third, we study algorithms for the temporal querying and incremental updating as well as dynamical management within the framework of TDIM.Based on a proper mathematical supporting, TDIM can be applied to researching some significant practical cases such as temporal relational and temporal XML data and so on.展开更多
文摘It is nontrivial to maintain such discovered frequent query patterns in real XML-DBMS because the transaction database of queries may allow frequent updates and such updates may not only invalidate some existing frequent query patterns but also generate some new frequent query patterns. In this paper, two incremental updating algorithms, FUX-QMiner and FUXQMiner, are proposed for efficient maintenance of discovered frequent query patterns and generation the new frequent query patterns when new XMI, queries are added into the database. Experimental results from our implementation show that the proposed algorithms have good performance. Key words XML - frequent query pattern - incremental algorithm - data mining CLC number TP 311 Foudation item: Supported by the Youthful Foundation for Scientific Research of University of Shanghai for Science and TechnologyBiography: PENG Dun-lu (1974-), male, Associate professor, Ph.D, research direction: data mining, Web service and its application, peerto-peer computing.
基金Supported by the National Natural Science Foundation of China (Grant Nos 60373081, 60673135)the Natural Science Foundation of Guangdong Province (Grant No 05003348)the Program of New Century Excellent Person Supporting of Ministery of Education of China(GrantNo.NCET-04-0805)
文摘This paper addresses the mathematical relation on a set of periods and temporal indexing construc- tions as well as their applications.First we introduce two concepts, i.e.the temporal connection and temporal inclusion, which are equivalence relation and preorder relation respectively.Second, by study- ing some basic topics such as the division of ＂large＂ equivalence classes and the overlaps of preorder relational sets, we propose a temporal data index model （TDIM） with a tree-structure consisting of a root node, equivalence class nodes and linearly ordered branch nodes.Third, we study algorithms for the temporal querying and incremental updating as well as dynamical management within the framework of TDIM.Based on a proper mathematical supporting, TDIM can be applied to researching some significant practical cases such as temporal relational and temporal XML data and so on.
