Nowadays, cloud data outsourcing provides users and companies with powerful capabilities to store and process their data in third-party data centers. However, the privacy of the outsourced data is not guaranteed by the cloud providers. One solution for protecting the user data against security attacks is to encrypt the data before being sent to the cloud servers. Then, the main problem is to ev...

This paper surveys recent studies of learning problems in which the learner faces restrictions on the amount of information he can extract from each example he encounters. Our main framework for the analysis of such scenarios is the RFA (Restricted Focus of Attention) model. While being a natural reenement of the PAC learning model, some of the fundamental PAC-learning results and techniques fa...

Top-k queries are widely applied for retrieving a ranked set of the k most interesting objects based on the individual user preferences. As an example, in online marketplaces, customers (users) typically seek a ranked set of products (objects) that satisfy their needs. Reversing top-k queries leads to a query type that instead returns the set of customers that find a product appealing (it belon...

Top-k query processing in P2P systems has focused on efficiently computing the top-k results while reducing network traffic and query response time. However, in overloaded P2P systems (with very high query loads), some peers may take a long time to answer, thus making the user wait a long time to obtain the final top-k result. In this paper, we address this problem, which we reformulate as earl...

Record linkage identifies multiple records referring to the same entity even if they are not bit-wise identical. It is thus an essential technology for data integration and data cleansing. Existing record linkage approaches are mainly relying on similarity functions based on the surface forms of the records, and hence are not able to identify complex coreference records. This seriously limits t...

Identifying the top-k most frequent elements is one of the many problems associated with data streams analysis. It is a well-known and difficult problem, especially if the analysis is to be performed and maintained up to date in near real time. Analyzing data streams in time sliding window model is of particular interest as only the most recent, more relevant events are considered. Approximate ...