Home Nonfiction 7 • New PDF release: Advances in Knowledge Discovery and Data Mining: 7th

New PDF release: Advances in Knowledge Discovery and Data Mining: 7th

By P. S. Bradley (auth.), Kyu-Young Whang, Jongwoo Jeon, Kyuseok Shim, Jaideep Srivastava (eds.)

ISBN-10: 3540047603

ISBN-13: 9783540047605

ISBN-10: 3540361758

ISBN-13: 9783540361756

The seventh Paci?c Asia convention on wisdom Discovery and information Mining (PAKDD) was once held from April 30 to may perhaps 2, 2003 within the conference and Ex- bition middle (COEX), Seoul, Korea. The PAKDD convention is a massive discussion board for tutorial researchers and practitioners within the Paci?c Asia quarter to proportion unique study effects and improvement reviews from di?erent KDD-related components similar to information mining, facts warehousing, laptop studying, databases, records, wisdom acquisition and discovery, info visualization, and knowledge-based platforms. The convention used to be prepared through the complex details expertise learn heart (AITrc) at KAIST and the Statistical examine middle for advanced structures (SRCCS) at Seoul nationwide collage. It used to be backed through the Korean Datamining Society (KDMS), the Korea Inf- mation technological know-how Society (KISS), the USA Air strength O?ce of Scienti?c study, the Asian O?ce of Aerospace examine & improvement, and KAIST. It used to be held with cooperation from ACM’s certain crew on wisdom Dis- very and information Mining (SIGKDD).

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Additional info for Advances in Knowledge Discovery and Data Mining: 7th Pacific-Asia Conference, PAKDD 2003, Seoul, Korea, April 30 – May 2, 2003 Proceedings

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An algorithm based on a window placement strategy is proposed to solve this problem. Future research includes data management issues and performance issues. In this paper, we only discuss existence pattern and sequential pattern. Other pattern formats can also be computed based on our basic idea. More temporal constraints can be added into mining process. The problems of how to select the appropriate window size and evaluate rules should also be investigated. For performance issues, as a query-based approach to creating the dataset is not efficient enough, the improvement of the efficiency of the algorithm is currently under the consideration.

Zhou most important event type in the sequence. We would like to identify all patterns of different types of recorded events (excluding or including the earthquake type itself) which potentially indicate the possibility of an earthquake situation. The temporal constraint would be then the length of the period of interest preceding the actual earthquake occurrence. Another application is telecommunication network fault analysis. A telecommunication network can be viewed as a hierarchical network, with switches, exchanges and transmission equipments.

We can examine all the paths including the event type hi from the event tree by following the linked list. Let us call the set of these paths Pi . These paths will help us to find the frequencies of episodes containing event type hi . , hH . The reason why we do not want to include hi+1 , ... , hH have been processed in earlier iterations. Let us call the set of all frequent episodes in DB that contain hi but not any of hi+1 , ... hH , the set Xi . We break up the Objective B into two smaller objectives: Objective B1: From the paths in Pi , we would like to find all frequent episodes in Xi of the form {a} ∪ {hi }, where a is a single event type.

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Advances in Knowledge Discovery and Data Mining: 7th Pacific-Asia Conference, PAKDD 2003, Seoul, Korea, April 30 – May 2, 2003 Proceedings by P. S. Bradley (auth.), Kyu-Young Whang, Jongwoo Jeon, Kyuseok Shim, Jaideep Srivastava (eds.)


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