Data uncertainty can be caused by numerous factors such as measurement precision limitations, network latency, data staleness and sampling errors. When mining knowledge from emerging applications such as sensor networks or location based services, data uncertainty should be handled cautiously to avoid erroneous results. In this paper, we apply probabilistic and statistical theory on uncertain d...

Web Usage Mining (WUM) is the process of extracting knowledge from Web user’s access data by exploiting Data Mining technologies. It can be used for different purposes such as personalization, system improvement and site modification. Study of interested web users, provides valuable information for web designer to quickly respond to their individual needs. The main objective of this paper is to...

Learning the structure of a Bayesian network from data is a difficult problem, as its associated search space is superexponentially large. As a consequence, researchers have studied learning Bayesian networks with a fixed structure, notably naive Bayesian networks and tree-augmented Bayesian networks, which involves no search at all. There is substantial evidence in the literature that the perf...

Bayesian network (BN) classifiers use different structures and different training parameters which leads to diversity in classification decisions. This work empirically shows that building an ensemble of several fine-tuned BN classifiers increases the overall classification accuracy. The accuracy of the constituent classifiers can be achieved by fine-tuning each classifier and the diversity is ...

The Bayesian network formalism is becoming increasingly popular in many areas such as decision aid, diagnosis and complex systems control, in particular thanks to its inference capabilities, evenwhen data are incomplete. Besides, estimating the parameters of a fixed-structure Bayesian network is easy. However, very few methods are capable of using incomplete cases as a base to determine the str...

Criminal behaviors can reflect the characteristics of the criminals to a great extent. To predict the crime types according to characteristics of vast amounts of criminals is an important part of criminal behavior analysis. In order to get high classification accuracy, three typical classification algorithms, including C4.5 algorithm, Naive Bayesian algorithm and K nearest neighbor (KNN) algori...