Continuous processing of preference queries in data streams

Abstract

Preference queries have received considerable attention in the recent past, due to their use in selecting the most preferred objects, especially when the selection criteria are contradictory. Nowadays, a significant number of applications require the manipulation of time evolving data and therefore the study of continuous query processing has recently attracted the interest of the data management community. The goal of continuous query processing is to continuously evaluate long-running queries by using incremental algorithms and thus to avoid query evaluation from scratch, if possible. In this paper, we examine the characteristics of important preference queries, such as skyline, top-k and top-k dominating and we review algorithms proposed for the evaluation of continuous preference queries under the sliding window streaming model. © 2010 Springer-Verlag Berlin Heidelberg.