Aggregation is among the core functionalities of OLAP systems. Frequently, such queries are issued in decision support systems to identify interesting groups of data. When more than one aggregation function is involved and the notion of interest is not clearly defined, skyline queries provide a robust mechanism to capture the potentially interesting points where (i) users do not need to specify...

In recent years, the skyline query paradigm has been established as a reliable and efficient method for database query personalization. While early efficiency problems have been approached, new challenges in its effectiveness continuously arise. Especially, the rise of the Semantic Web and linked open data leads to personalization issues where skyline queries cannot be applied easily. In fact, ...

A skyline query is useful for extracting a complete set of interesting tuples from a large data set according to multiple criteria. The sizes of data sets are constantly increasing and the architecture of backends are switching from single node environments to cluster oriented setups. Previous work has presented ways to run the skyline query in these setups using the MapReduce framework, but th...

We propose to extend database systems by a Skyline operation. This operation filters out a set of interesting points from a potentially large set of data points. A point is interesting if it is not dominated by any other point. For example, a hotel might be interesting for somebody traveling to Nassau if no other hotel is both cheaper and closer to the beach. We show how SQL can be extended to ...

several open questions. Most pertinently: how do ants encode skyline information? And, how do ants derive a movement direction from the comparison of their current skyline view and their remembered view? Recent experiments, also with M. bagoti [10], have addressed the first question. By masking different portions of the visual panorama, it was possible to show that being able to view prominent ...

Preference-based queries (or skylines) play an important role in cooperative query processing. However, their prohibitive result sizes pose a severe challenge to the paradigm’s practical applicability. Since skyline sizes can only be predicted under strong assumptions, we present a sophisticated user interface to interactively refine queries in case the respective skyline set proves to be too l...

Cooperative database retrieval is a challenging problem: top k retrieval delivers manageable results only when a suitable compensation function (e.g. a weighted mean) is explicitly given. On the other hand skyline queries offer intuitive querying to users, but result set sizes grow exponentially and hence can easily exceed manageable levels. We show how to combine the advantages of skyline quer...

Marine monitoring systems have the requirements of a large field of view, low power consumption, real-time viewing, and economical and automatic functionality. This paper establishes an omnidirectional vision system used in marine buoys that meets these requirements. We present a framework for image stabilization, which is achieved by omnidirectional sea-skyline detection in a marine environmen...

Today, result sets of skyline queries are unmanageable due to their exponential growth with the number of query predicates. In this paper we discuss the incremental re-computation of skylines based on additional information elicited from the user. Extending the traditional case of totally ordered domains, we consider preferences in their most general form as strict partial orders of attribute v...