Mining Level-Crossing Association Rules from Large Databases
نویسندگان
چکیده
منابع مشابه
Mining Level-Crossing Association Rules from Large Databases
Existing algorithms for mining association rule at multiple concept level, restricted mining strong association among the concept at same level of a hierarchy. However mining level-crossing association rule at multiple concept level may lead to the discovery of mining strong association among at different level of hierarchy. In this study, a top-down progressive deepening method is developed fo...
متن کاملMining Multiple-Level Association Rules in Large Databases
ÐA top-down progressive deepening method is developed for efficient mining of multiple-level association rules from large transaction databases based on the Apriori principle. A group of variant algorithms is proposed based on the ways of sharing intermediate results, with the relative performance tested and analyzed. The enforcement of different interestingness measurements to find more intere...
متن کاملDiscovery of Multiple-Level Association Rules from Large Databases
Discovery of association rules from large databases has been a focused topic recently in the research into database mining. Previous studies discover association rules at a single concept level, however, mining association rules at multiple concept levels may lead to nding more informative and re ned knowledge from data. In this paper, we study e cient methods for mining multiple-level associat...
متن کاملMining Condensed Non-Redundant Level-Crossing Approximate Association Rules
In association rule mining one intractable problem is the huge number of the extracted rules, especially, in the case of level-crossing association rules. In this paper, aiming at the redundancy produced during level-crossing association rules mining, an approach for eliminating level-crossing approximate redundant rules is proposed. In the method, the redundancies are divided combination with ...
متن کاملMining association rules from biological databases
area such as bioinformatics. This methodology allows the identification of relationships between low-magnitude similarity (LMS) sequence patterns and other well-contrasted protein characteristics, such as those described by database annotations. We start with the identification of these signals inside protein sequences by exhaustive database searching and automatic pattern recognition strategie...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computer Science
سال: 2006
ISSN: 1549-3636
DOI: 10.3844/jcssp.2006.76.81