Many recent applications involve processing and analyzing uncertain data. In this paper, we combine the feature of top-k objects with that of skyline to model the problem of top-k skyline objects against uncertain data. The problem of efficiently computing top-k skyline objects on large uncertain datasets is challenging in both computing the top-k skyline objects is developed for discrete cases...

The top-k skyline groups query (k-SGQ) returns k skyline groups that dominate the maximum number of points in a given data set. It combines the advantages of skyline groups and top-k queries. The k-SGQ is an important tool for queries that need to analyze not only individual points but also groups of points, and can be widely used in areas such as decision support applications, market analysis ...

We propose an integrated approach for solving both problems of finding the most popular k elements, and finding frequent elements in a data stream. Our technique is efficient and exact if the alphabet under consideration is small. In the more practical large alphabet case, our solution is space efficient and reports both top-k and frequent elements with tight guarantees on errors. For general d...

Top-k queries are attractive for users in P2P systems with very large numbers of peers but difficult to support efficiently. In this paper, we propose a fully distributed algorithm for executing Top-k queries in the context of the APPA (Atlas Peer-to-Peer Architecture) data management system. APPA has a network-independent architecture that can be implemented over various P2P networks. Our algo...

Ranking queries, also known as top-k queries, have drawn considerable attention due to their usability in various applications. Several algorithms have been proposed for the evaluation of top-k queries. A large percentage of them follow the Threshold Approach. In p2p networks, top-k query processing can provide a lot of advantages both in time and bandwidth consumption. We focus on the main ada...

Top-k is the most important query type in OLAP, a common data warehouses model. Recently, OLAP was extended to represent data ambiguity, specifically imprecision and uncertainty. However, how to deal with top-k queries in uncertain OLAP still remains an unanswered question. This project introduces a solution for top-k query evaluation in uncertain OLAP including query semantic definition, query...

Top-k is the most important query type in OLAP, the most common data warehouses model. Recently, OLAP was extended to represent data ambiguity, specifically imprecision and uncertainty. However, how to deal with top-k queries in uncertain OLAP still remain an unanswered question. This project introduces a complete solution for top-k query in uncertain OLAP including query semantic definition, q...

The Top-K problem is defined as follows. Given L lists of real numbers, find the top K scoring L-tuples. A tuple is scored by the sum of its components. Rare event modeling and event ranking are often reduced to the Top-K problem. In this paper, we present the application of a fixedmemory heuristic search algorithm (namely, SMA*) and its distributed-memory extension to the Top-K problem. Our ap...

In this paper, we present a simple yet effective algorithm, called the Top-k Case Matching algorithm, for the imputation of missing values in streams of time series data that are similar to each other. The key idea of the algorithm is to look for the k situations in the historical data that are most similar to the current situation and to derive the missing value from the measured values at the...