The amount of data produced by ubiquitous computing applications is quickly growing, due to the pervasive presence of small devices endowed with sensing, computing and communicatio...
Annalisa Appice, Michelangelo Ceci, Antonio Turi, ...
Abstract. This paper describes an approach to identifying and comparing frequent pattern trends in social networks. A frequent pattern trend is defined as a sequence of time-stampe...
Puteri N. E. Nohuddin, Rob Christley, Frans Coenen...
The mining of frequent patterns in databases has been studied for several years. However, the real-world data tends to be dirty and frequent pattern mining which extracts patterns...
Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent...
Discovering frequent patterns from data is a popular exploratory technique in data mining. However, if the data are sensitive (e.g. patient health records, user behavior records) ...
Raghav Bhaskar, Srivatsan Laxman, Adam Smith, Abhr...
Mining frequent patterns is a major topic in data mining research, resulting in many seminal papers and algorithms on item set and episode discovery. The combination of these, call...
Frequent pattern mining has been studied extensively. However, the effectiveness and efficiency of this mining is often limited, since the number of frequent patterns generated i...
In this paper, we propose a new mining task: mining top-k frequent closed patterns of length no less than min , where k is the desired number of frequent closed patterns to be min...
Mining frequent patterns has been a topic of active research because it is computationally the most expensive step in association rule discovery. In this paper, we discuss the use ...
Scalable data mining in large databases is one of today’s real challenges to database research area. The integration of data mining with database systems is an essential componen...