Dynamic maintenance model for high average-utility pattern mining with deletion operation
نویسندگان
چکیده
منابع مشابه
A New Algorithm for High Average-utility Itemset Mining
High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold. The basic HUIM problem does not consider length of itemsets in its utility measurement and utility values tend to become higher for itemsets containing more items...
متن کاملHigh-Utility Sequential Pattern Mining with Multiple Minimum Utility Thresholds
High-utility sequential pattern mining is an emerging topic in recent decades and most algorithms were designed to identify the complete set of high-utility sequential patterns under the single minimum utility threshold. In this paper, we first propose a novel framework called high-utility sequential pattern mining with multiple minimum utility thresholds to mine high utility sequential pattern...
متن کاملMining High Average-Utility Itemsets with an Indexed Projection Technique
An itemset in traditional utility mining only considers individual profits and quantities of items in transactions but not its itemset length. The average-utility measure, which is the total utility of an itemset divided by its number of items within it, was then proposed to reveal a better utility effect than the original utility one. However, their proposed approach was based on the principle...
متن کاملEffective utility mining with the measure of average utility
Tzung-Pei Hong , Cho-Han Lee and Shyue-Liang Wang Department of Computer Science and Information Engineering Department of Electrical Engineering Department of Information Management National University of Kaohsiung, Kaohsiung, 811, Taiwan Department of Computer Science and Engineering National Sun Yat-sen University, Kaohsiung, 804, Taiwan [email protected], [email protected], slwang@nu...
متن کاملMemory-Bounded High Utility Sequential Pattern Mining over Data Streams
Mining high utility sequential patterns (HUSPs) has emerged as an important topic in data mining. However, the existing studies on this topic focus on static data and do not consider streaming data. Streaming data are fast changing, continuously generated and unbounded in amount. Such data can easily exhaust computer resources (e.g., memory) unless proper resource-aware mining is performed. In ...
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: Applied Intelligence
سال: 2021
ISSN: 0924-669X,1573-7497
DOI: 10.1007/s10489-021-02539-4