Konstantinos Zoumpatianos

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Numerous applications continuously produce big amounts of data series, and in several time critical scenarios analysts need to be able to query these data as soon as they become available, which is not currently possible with the state-of-the-art indexing methods and for very large data series collections. In this paper, we present the first adaptive(More)
Numerous applications continuously produce big amounts of data series, and in several time critical scenarios analysts need to be able to query these data as soon as they become available. An adaptive index data structure, ADS+, which is specifically tailored to solve the problem of indexing and querying very large data series collections has been recently(More)
The aim of this paper is to present a novel technological approach for enhancing the collective knowledge of communities of learners on the engineering of ontologies within a collaborative, open and socially constructed environment. The proposed technology aims at shaping information spaces into ontologies in a collaborative, communicative and(More)
Even though much research has been devoted on real-time data warehousing, most of it ignores business concerns that underlie all uses of such data. The complete Business Intelligence (BI) problem begins with modeling and analysis of business objectives and specifications, followed by a systematic derivation of real-time BI queries on warehouse data. In this(More)
Data series are a prevalent data type that has attracted lots of interest in recent years. Most of the research has focused on how to efficiently support similarity or nearest neighbor queries over large data series collections (an important data mining task), and several data series summarization and indexing methods have been proposed in order to solve(More)
Numerous applications continuously produce big amounts of data series, and in several time critical scenarios analysts need to be able to query these data as soon as they become available. This, however, is not currently possible with the state-of-the-art indexing methods and for very large data series collections. In this paper, we present the first(More)
Modeling the strategic objectives has been shown to be useful both for understanding a business as well as planning and guiding the overall activities within an enterprise. Business strategy is modeled according to human expertise, setting up the goals as well as the indicators that monitor activities and goals. However, usually indicators provide(More)
Business analytics has emerged in the past decade as a top concern for business executives world-wide, surpassing earlier top concerns such as supply chain management and total quality management. Business analysis techniques analyze operational data for a variety of purposes including prediction, planning, monitoring, and trouble-shooting. In this paper we(More)