A5064647811- Advanced Database Systems and Queries
- Peer-to-Peer Network Technologies
- Advanced Data Storage Technologies
- Data Management and Algorithms
- Semantic Web and Ontologies
- Caching and Content Delivery
- Natural Language Processing Techniques
- Web Data Mining and Analysis
- Data Mining Algorithms and Applications
- Topic Modeling
- Opportunistic and Delay-Tolerant Networks
- Distributed and Parallel Computing Systems
- Text and Document Classification Technologies
- Scientific Computing and Data Management
- Service-Oriented Architecture and Web Services
- IoT and Edge/Fog Computing
- Machine Learning in Materials Science
- Catalytic Processes in Materials Science
- Algorithms and Data Compression
- Network Security and Intrusion Detection
- Data Quality and Management
- Distributed Sensor Networks and Detection Algorithms
- Cooperative Communication and Network Coding
- Machine Learning and Algorithms
Ionian University
2022
École Polytechnique Fédérale de Lausanne
2020
Max Planck Institute for Informatics
2011-2013
Inria Saclay - Île de France
2008-2011
Laboratoire de Recherche en Informatique
2010-2011
Université Paris-Sud
2008-2011
Max Planck Society
2011
Institut national de recherche en informatique et en automatique
2008-2010
Knowledge Integration (United Kingdom)
2007-2009
Materials Cloud is a platform designed to enable open and seamless sharing of resources for computational science, driven by applications in materials modelling. It hosts 1) archival dissemination services raw curated data, together with their provenance graph, 2) modelling virtual machines, 3) tools data analytics, pre-/post-processing, 4) educational materials. Data citable archived persistently, providing comprehensive embodiment the FAIR principles that extends workflows. leverages AiiDA...
Abstract The ever-growing availability of computing power and the sustained development advanced computational methods have contributed much to recent scientific progress. These developments present new challenges driven by sheer amount calculations data manage. Next-generation exascale supercomputers will harden these challenges, such that automated scalable solutions become crucial. In years, we been developing AiiDA (aiida.net), a robust open-source high-throughput infrastructure...
Mobile networks experience a tremendous increase in data volume and user density due to the massive number of coexisting users devices. An efficient technique alleviate this issue is bring closer by exploiting cache-aided edge nodes, such as fixed mobile access points, even Meanwhile, fusion machine learning wireless offers new opportunities for network optimization when traditional approaches fail or incur high complexity. Among various categories, reinforcement provides autonomous...
Frequent sequence mining is one of the fundamental building blocks in data mining. While problem has been extensively studied, few available techniques are sufficiently scalable to handle datasets with billions sequences; such large-scale arise, for instance, text and session analysis. In this paper, we propose MG-FSM, a algorithm frequent on MapReduce. MG-FSM can so-called "gap constraints", which be used limit output controlled set sequences. At its heart, partitions input database way...
SIGMOD 2008 was the first database conference that offered to test submitters' programs against their data verify experiments published. This paper discusses rationale for this effort, community's reaction, our experiences, and advice future similar efforts.
We consider the problem of rewriting XQuery queries using multiple materialized views. The dialect we use to express views and corresponds tree patterns (returning data from several nodes, at different granularities, ranging node identifiers full XML subtrees) with value joins. provide correct complete algorithms for finding minimal rewritings, in which no view is redundant. Our work extends state art by considering more flexible than mostly XPath 1.0 dialects previously considered, powerful...
The evolution of natural language processing (NLP) has drastically improved numerous applications in terms quality results and speed, like the use semantic search modern engines. NLP highly benefited from recent developments word sentence embeddings which enable transformation complex tasks, such as similarity or Question Answering (Q&A), into much simpler to perform vector comparisons. However, new problems resulting transformations have also challenging tasks address efficient comparison...
We present the WebContent platform for managing distributed repositories of XML and semantic Web data. The allows integrating various data processing building blocks (crawling, translation, annotation, full-text search, structured querying, querying), presented as services, into a large-scale efficient platform. Calls to services are combined inside ActiveXML [8] documents, which documents including service calls. An optimizer is used to: ( i ) efficiently distribute computations among...
The Web has become a platform of choice for the deployment complex applications involving several business partners. Typically, such interoperate by means services, exchanging XML information. We present OptimAX, an optimization service that applies at static level (prior to enacting application) in order rewrite it into one whose execution will be more performant. OptimAX builds on ActiveXML (AXML) data-centric composition language, and demonstrates how database-style techniques can...
Knowledge harvesting enables the automated construction of large knowledge bases. In this work, we made a first attempt to harvest spatio-temporal from news archives construct trajectories individual entities for entity tracking. Our approach consists an extraction and disambiguation module fact generation which produce pertinent trajectory records textual sources. The evaluation on 20 years' New York Times article corpus showed that our methods are effective scalable.
Mash-ups are being used in various Web-based applications of Web 2.0 which combine instantly information from different sources. Active XML (AXML, short) language is a tool for decentralized, data-centric service integration. AXML document includes calls to services that may be either simple request-responses long running subscriptions. Being fully composable and allowing resource sharing makes ideal mash-up style In this demo we present how can as specification, optimization distributed...
The proliferation of electronic content has notably lead to the apparition large corpora interrelated structured documents (such as HTML and XML Web pages) semantic annotations (typically expressed in RDF), which further complement these documents. Documents may be authored independently by different users or programs. We present AnnoVIP, a peer-to-peer platform, capable efficiently exploiting multitude annotated documents, based on innovative materialized views.
Mobile networks are experiencing tremendous increase in data volume and user density. An efficient technique to alleviate this issue is bring the closer users by exploiting caches of edge network nodes, such as fixed or mobile access points even devices. Meanwhile, fusion machine learning wireless offers a viable way for optimization opposed traditional approaches which incur high complexity, fail provide optimal solutions. Among various categories, reinforcement operates an online...
The growing volumes of XML data sources on the Web or produced by enterprises, organizations etc. raise many performance challenges for management applications. In this work, we are concerned with distributed, peer-to-peer large corpora documents, based distributed hash table (or DHT, in short) overlay networks. We present ViP2P (standing Views Peer-to-Peer), a platform sharing documents structured P2P network infrastructure (DHT). At core stand materialized views, defined arbitrary queries,...