A biclustering algorithm, based on a greedy technique and enriched with a local search strategy to escape poor local minima, is proposed. The algorithm starts with an initial rando...
Data mining techniques frequently find a large number of patterns or rules, which make it very difficult for a human analyst to interpret the results and to find the truly interes...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Weimin Xia...
The number of web pages available on Internet increases day after day, and consequently finding relevant information becomes more and more a hard task. However, when we consider ...
Aliaksandr Birukou, Enrico Blanzieri, Paolo Giorgi...
Meta-learning system for KDD is an open and evolving platform for efficient testing and intelligent recommendation of data mining process. Metalearning is adopted to automate the s...
Abstract. This paper proposes a new support vector machine (SVM) with a robust loss function for data mining. Its dual optimal formation is also constructed. A gradient based algor...
Execution cost of batched data mining queries can be reduced by integrating their I/O steps. Due to memory limitations, not all data mining queries in a batch can be executed toget...
Accurate probability-based ranking of instances is crucial in many real-world data mining applications. KNN (k-nearest neighbor) [1] has been intensively studied as an effective c...
In real-world data mining applications, an accurate ranking is same important to a accurate classification. Naive Bayes (simply NB) has been widely used in data mining as a simple...
Liangxiao Jiang, Harry Zhang, Zhihua Cai, Jiang Su
: Artificial Immune Systems are a new class of algorithms inspired by how the immune system recognizes, attacks and remembers intruders. This is a fascinating idea, but to be accep...
In this paper, we design genetic algorithm and simulated annealing algorithm and their parallel versions to solve the Closest String problem. Our implementation and experiments sho...