There has been much interest in answering top-k queries on probabilistic data in various applications such as market analysis, personalised services, and decision making. In relation to probabilistic data, the most common problem in answering top-k queries is selecting the semantics of results according to their scores and top-k probabilities. In this paper, we propose a novel top-k best probab...

Continuous monitoring of spatial queries has gained significant research attention in the past few years. Although numerous algorithms have been proposed to solve specific queries, there does not exist a unified algorithm that solves a broad class of spatial queries. In this paper, we first define a versatile top-k query and show that various important spatial queries can be modeled to a versat...

Top-k query has been widely studied recently in many applied fields. Fagin et al. [3] proposed an efficient algorithm, the Threshold Algorithm (i.e. TA), to process top-k queries. However, in many cases, TA does not terminate even if the final top-k results have been found for some time. Based on these, we propose a novel algorithm: Density Threshold Algorithm (i.e. DTA), which is designed to m...

Top-k query processing finds a list of k results that have largest scores w.r.t the user given query, with the assumption that all the k results are independent to each other. In practice, some of the top-k results returned can be very similar to each other. As a result some of the top-k results returned are redundant. In the literature, diversified top-k search has been studied to return k res...

There has been much interest in answering top-k queries on probabilistic data in various applications such as market analysis, personalised services, and decision making. In probabilistic relational databases, the most common problem in answering top-k queries (ranking queries) is selecting the top-k result based on scores and top-k probabilities. In this paper, we firstly propose novel answers...

With the generation and analysis of stream data, such as network monitoring in real time, log records, click streams, a great deal of attention has been concerned on data streams mining in the field of data mining. In the process of the data streams mining, it is more reasonable to ask users to set a bound on the result size. Therefore, in this paper, an real-time single-pass algorithm, called ...

Top-k pairs and top-k objects queries have received significant attention by the research community. In this paper, we present the first approach to answer a broad class of top-k pairs and top-k objects queries over sliding windows. Our framework handles multiple top-k queries and each query is allowed to use a different scoring function, a different value of k and a different size of the slidi...

Top-k query in a wireless sensor network is to identify k sensors with the highest sensor readings. Since sensors usually are powered by energy-limited batteries, a fundamental problem associated with top-k query evaluation in such a network is to maximize network lifetime, which poses great challenges due to the unique characteristics of sensor networks. In this paper, we first propose a novel...

We tackle the problem of maintaining materialized topk views in this paper. Top-k queries, including MIN and MAX as important special cases, occur frequently in common database workloads. A top-k view can be materialized to improve query performance, but in general it is not selfmaintainable unless it contains all tuples in the base table. Deletions and updates on the base table may cause tuple...