Framework for Managing Uncertain Distributed Categorical Data

Indexing Uncertain Categorical Data over Distributed Environment

Today, a large amount of uncertain data is produced by several applications where the management systems of traditional databases including indexing methods are not suitable to handle such type of data. In this paper, we propose an inverted based index method for efficiently searching uncertain categorical data over distributed environments. We address two kinds of query over the distributed un...

Managing and Mining Uncertain Data Managing and Mining Uncertain Data

In recent years, uncertain data has become ubiquitous because of new technologies for collecting data which can only measure and collect the data in an imprecise way. Furthermore, many technologies such as privacy-preserving data mining create data which is inherently uncertain in nature. As a result there is a need for tools and techniques for mining and managing uncertain data. This chapter d...

A Framework for Filtering News and Managing Distributed Data

With the development and di usion of the Internet worldwide connection, a large amount of information is available to the users. Methods of information ltering and fetching are then required. This paper presents two approaches. The rst concerns the information ltering system ProFile based on an adaptation of the generalized probabilistic model of information retrieval. ProFile lters the netnews...

ORION: Managing Uncertain (Sensor) Data

An important quality of sensor data is that it is often uncertain or imprecise. This uncertainty can be an inherent aspect of the data (e.g. due to known errors in the measuring device, such as the Gaussian error in GPS readings), or it may be introduced in order to achieve scalability [2, 1], or to ensure a certain level of privacy [4]. Existing database management systems provide virtually no...

Managing and Mining Uncertain Data