Uncertain data have already widely existed in many practical applications recently, such as
sensor networks, RFID networks, location-based services, and mobile object management …

We consider the problem of parameter estimation in statistical models in the case where
data are uncertain and represented as belief functions. The proposed method is based on …

Skewed class proportions in real-world datasets present a challenge for machine learning
algorithms, as they have a tendency to correctly categorize the majority class while …

Uncertain data are data with uncertainty information, which exist widely in database
applications. In recent years, uncertainty in data has brought challenges in almost all …

Reverse top-k queries are proposed from the perspective of a product manufacturer, which
are essential for manufacturers to assess the potential market. However, the existing …

There has been an increasing growth in numerous applications that naturally generate large
volumes of uncertain data. By the advent of such applications, the support of advanced …

Given a set of users, a set of facilities and a query facility q, a reverse k nearest neighbors (R
k NN) query returns every user u for which the query is one of its k closest facilities. R k NN …

We propose and study a new type of facility location selection query, the top-k most
influential location selection query. Given a set M of customers and a set F of existing …

Given a query object q, a reverse nearest neighbor (RNN) query in a common certain
database returns the objects having q as their nearest neighbor. A new challenge for …

The location selection (LS) problem identifies an optimal site to place a new facility such that
its influence on given objects can be maximized. With the proliferation of GPS-enabled …