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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)
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)
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)
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 " ,(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)
Bloom filter based algorithms have proven successful as very efficient technique to reduce communication costs of database joins in a distributed setting. However, the full potential of bloom filters has not yet been exploited. Especially in the case of multi-joins, where the data is distributed among several sites, additional optimization opportunities(More)
Distributed joins have gained importance in the past decade, mainly due to the increased number of available data sources on the Internet. In this work we extend Bloomjoin, the state of the art algorithm for distributed joins, so that it minimizes the network usage for the query execution based on database statistics. We present 4 extensions of the(More)