Odysseas Papapetrou

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While traditional data-management systems focus on evaluating single, adhoc queries over static data sets in a centralized setting, several emerging applications require (possibly, continuous) answers to queries on dynamic data that is widely distributed and constantly updated. Furthermore, such query answers often need to discount data that is “stale”, and(More)
Modeling competences is an integral part of many Human Resource (HR) and e-Learning related activities. HR departments use competence descriptions to define requirements needed for performing specific tasks or jobs. The same competences are acquired by employees and applicants by e.g. experience or certifications. Typically, HR departments need to match(More)
Bloom filters are extensively used in distributed applications, especially in distributed databases and distributed information systems, to reduce network requirements and to increase performance. In this work, we propose two novel Bloom filter features that are important for distributed databases and information systems. First, we present a new approach to(More)
We consider a data owner that outsources its dataset to an untrusted server. The owner wishes to enable the server to answer range queries on a single attribute, without compromising the privacy of the data and the queries. There are several schemes on "practical" private range search (mainly in Databases venues) that attempt to strike a trade-off between(More)
Mining frequent subgraph patterns in graph databases is a challenging and important problem with applications in several domains. Recently, there is a growing interest in generalizing the problem to <i>uncertain graphs</i>, which can model the inherent uncertainty in the data of many applications. The main difficulty in solving this problem results from the(More)
Distributed crawling has shown that it can overcome important limitations of the centralized crawling paradigm. However, the distributed nature of current distributed crawlers is currently not fully utilized. The optimal benefits of this approach are usually limited to the sites hosting the crawler. In this work we describe IPMicra, a distributed location(More)
Distributed hash tables (DHTs) are very efficient for querying based on key lookups. However, building huge term indexes, as required for IR-style keyword search, poses a scalability challenge for plain DHTs. Due to the large sizes of document term vocabularies, peers joining the network cause huge amounts of key inserts and, consequently, a large number of(More)
Distributed skyline computation is important for a wide range of application domains, from distributed and web-based systems to ISP-network monitoring and distributed databases. The problem is particularly challenging in dynamic distributed settings, where the goal is to efficiently monitor a continuous skyline query over a collection of distributed(More)
While traditional data management systems focus on evaluating single, ad hoc queries over static data sets in a centralized setting, several emerging applications require (possibly, continuous) answers to queries on dynamic data that is widely distributed and constantly updated. Furthermore, such query answers often need to discount data that is “stale” and(More)
Aspect Oriented Programming, a relatively new programming paradigm, earned the scientific community's attention. The paradigm is already evaluated for traditional OOP and component-based software development with remarkable results. However, most of the published work, while of excellent quality, is mostly theoretical or involves evaluation of AOP for(More)