Develo** recommender systems with the consideration of product profitability for sellers
In electronic commerce web sites, recommender systems are popularly being employed to
help customers in selecting suitable products to meet their personal needs. These systems …
help customers in selecting suitable products to meet their personal needs. These systems …
Mining frequent itemsets over data streams using efficient window sliding techniques
HF Li, SY Lee - Expert systems with applications, 2009 - Elsevier
Online mining of frequent itemsets over a stream sliding window is one of the most important
problems in stream data mining with broad applications. It is also a difficult issue since the …
problems in stream data mining with broad applications. It is also a difficult issue since the …
Sliding window-based frequent pattern mining over data streams
Finding frequent patterns in a continuous stream of transactions is critical for many
applications such as retail market data analysis, network monitoring, web usage mining, and …
applications such as retail market data analysis, network monitoring, web usage mining, and …
Neighborhood rough sets for dynamic data mining
Approximations of a concept in rough set theory induce rules and need to update for
dynamic data mining and related tasks. Most existing incremental methods based on the …
dynamic data mining and related tasks. Most existing incremental methods based on the …
Efficient mining of weighted interesting patterns with a strong weight and/or support affinity
Most algorithms for frequent pattern mining use a support constraint to prune the
combinatorial search space but support-based pruning is not enough. After mining datasets …
combinatorial search space but support-based pruning is not enough. After mining datasets …
Mining frequent trajectory patterns in spatial–temporal databases
In this paper, we propose an efficient graph-based mining (GBM) algorithm for mining the
frequent trajectory patterns in a spatial–temporal database. The proposed method …
frequent trajectory patterns in a spatial–temporal database. The proposed method …
Verifying and mining frequent patterns from large windows over data streams
Mining frequent itemsets from data streams has proved to be very difficult because of
computational complexity and the need for real-time response. In this paper, we introduce a …
computational complexity and the need for real-time response. In this paper, we introduce a …
Minimal infrequent pattern based approach for mining outliers in data streams
Outlier detection is an important task in data mining which aims at detecting patterns that are
unusual in a dataset. Though several techniques are proved to be useful in solving some …
unusual in a dataset. Though several techniques are proved to be useful in solving some …
Mining spatial association rules in image databases
In this paper, we propose a novel spatial mining algorithm, called 9DLT-Miner, to mine the
spatial association rules from an image database, where every image is represented by the …
spatial association rules from an image database, where every image is represented by the …
A sliding window based algorithm for frequent closed itemset mining over data streams
Frequent pattern mining over data streams is an important problem in the context of data
mining and knowledge discovery. Mining frequent closed itemsets within sliding window …
mining and knowledge discovery. Mining frequent closed itemsets within sliding window …