@conference {826, title = {EnQuest: A Cloud Datalake Infrastructure for Heterogeneous Analytics in Maritime and Tourism Domains}, booktitle = {DATA 2023 (demo)}, year = {2023}, abstract = {

Within recent years, transportation and supply chain have been affected by an avalanche of data including IoT devices, online services, social media and others. However, the implemented solutions so far are fragmented, physically distributed, require specialized IT knowledge to deploy, and involve significant IT experience to operate even for trivial tasks. In the context of the ENIRISST+ project, we developed EnQuest1, an online data lake that allows users without any IT background to harvest, store, organize, analyze and share heterogeneous, multi-faceted maritime/tourism data. EnQuest provides a zero-administration, zero-cost, integrated framework that enables scientists, practitioners and other stakeholders within the above domains to easily: (i) deploy data acquisition services (crawlers, dataset imports, questionnaire forms), (ii) design and manage versatile customizable data stores, (iii) share whole datasets or horizontal/vertical data shards with other stakeholders, (iv) search, filter and analyze data via an expressive yet simple-to-use graphical query engine and visualization tools, and (v) perform user management and access control operations on the stored data. To the best of our knowledge, this is the first approach in the literature that targets users without an IT background and focuses on collecting, managing, analyzing, and sharing diverse, multi-faceted data in maritime the and tourism sectors. The main goals of the proposed demonstration are to showcase the EnQuest system to the conference participants and promote the work of the ENIRISST+ project consortium. During the demo we will (i) deploy social media crawlers to gather maritime data and show the participants how to process and visualise them, (ii) create live questionnaires using the EnQuest functionality, ask the participants to fill them in and demonstrate the live processed data on appropriate dashboards, and (iii) demonstrate how to import data and subscribe to data flows of other users through the implemented publish/subscribe module. For the needs of the demo we will only require internet connection and a desk; we will have our own laptops to use at the demonstration.

}, keywords = {big data, cloud systems, data analytics, datalakes, maritime, tourism}, author = {Kimon Deligiannis and Christos Tryfonopoulos and Paraskevi Raftopoulou and Nikos Platis and Costas Vassilakis} } @conference {821, title = {RoG: A Pipeline for Automated Sensitive Data Identification and Anonymisation}, booktitle = {Proceedings of the 2023 IEEE CSR Workshop on Data Science for Cyber Security (DS4CS)}, year = {2023}, abstract = {

Nowadays, the amount of data available online is constantly increasing. This data may contain sensitive or private information that can expose the person behind the data or be misused by malicious actors for identity theft, stalking, and other nefarious purposes. There is thus, a growing need to protect individuals{\textquoteright} privacy and prevent data breaches in several application domains. Protecting data privacy though, is a complex and multifaceted issue that involves a range of legal, ethical, and technical considerations. In this paper, we discuss the challenges associated with data protection, the role of automated tools, and the effectiveness of identifying and anonymising sensitive data. We then, propose a fully-automated process for sensitive data identification and anonymisation, based on Natural Language Processing (NLP) techniques, that can be applied both in big diverse datasets and to a wide range of domains.

}, keywords = {anonymisation, automated process, k-anonymity, NER, NLP, pipeline, sensitive/private data}, author = {Sotiris Nikoletos and Stefanos Vlachos and Efstathios Zaragkas and Costas Vassilakis and Christos Tryfonopoulos and Paraskevi Raftopoulou} } @conference {819, title = {SodaSense: An Intelligence Platform for Micro-Mobility, Micro-Climate and Agriculture}, booktitle = {Proceedings of the GEOProcessing 2023}, year = {2023}, abstract = {

SODASENSE is an end-to-end big data manipulation platform that focuses on decision and policy making. It concerns the management of big trajectory and spatio-temporal data that is collected from sensors and relates to micro-mobility, microclimate and agriculture, and aims to the creation of an expert decision making platform with research, social and business orientation.

}, keywords = {big data management and analysis, spatial time series, trajectories}, author = {Paraskevi Raftopoulou and Spiros Skiadopoulos and Christos Tryfonopoulos and Costas Vasilakis} } @article {772, title = {Hydria: An Online Data Lake for Multi-Faceted Analytics in the Cultural Heritage Domain}, journal = {Big Data and Cognitive Computing}, volume = {4}, year = {2020}, pages = {7}, abstract = {Advancements in cultural informatics have significantly influenced the way we perceive, analyze, communicate and understand culture. New data sources, such as social media, digitized cultural content, and Internet of Things (IoT) devices, have allowed us to enrich and customize the cultural experience, but at the same time have created an avalanche of new data that needs to be stored and appropriately managed in order to be of value. Although data management plays a central role in driving forward the cultural heritage domain, the solutions applied so far are fragmented, physically distributed, require specialized IT knowledge to deploy, and entail significant IT experience to operate even for trivial tasks. In this work, we present Hydria, an online data lake that allows users without any IT background to harvest, store, organize, analyze and share heterogeneous, multi-faceted cultural heritage data. Hydria provides a zero-administration, zero-cost, integrated framework that enables researchers, museum curators and other stakeholders within the cultural heritage domain to easily (i) deploy data acquisition services (like social media scrapers, focused web crawlers, dataset imports, questionnaire forms), (ii) design and manage versatile customizable data stores, (iii) share whole datasets or horizontal/vertical data shards with other stakeholders, (iv) search, filter and analyze data via an expressive yet simple-to-use graphical query engine and visualization tools, and (v) perform user management and access control operations on the stored data. To the best of our knowledge, this is the first solution in the literature that focuses on collecting, managing, analyzing, and sharing diverse, multi-faceted data in the cultural heritage domain and targets users without an IT background.}, keywords = {analytics and visualization, big data management, Cultural heritage, data lake, data store, open source}, doi = {10.3390/bdcc4020007}, url = {https://www.mdpi.com/2504-2289/4/2/7}, author = {Kimon Deligiannis and Paraskevi Raftopoulou and Christos Tryfonopoulos and Nikos Platis and Costas Vassilakis} } @conference {545, title = {Data Science Tutor: An online platform for automated exercise solving in Data Science}, booktitle = {Proceedings of the 9th Conference on Computer Science Teaching (DIDINFO)}, year = {2018}, month = {October}, address = {Thessaloniki, Greece}, author = {Christos Tryfonopoulos and Charis Kotsiopoulos and Paraskevi Raftopoulou} } @conference {541, title = {Towards Content-Based Publish/Subscribe for Distributed Social Networks}, booktitle = {Proceedings of the International Conference on Distributed Event-Based Systems (DEBS)}, year = {2015}, month = {June}, address = {Oslo, Norway}, author = {Christos Tryfonopoulos and Paraskevi Raftopoulou and Vinay Setty and Argiris Xiros} } @article {582, title = {Distributed Large-Scale Information Filtering}, journal = {Transactions on Large-Scale Data- and Knowledge-Centered Systems (TLDKS)}, volume = {13}, year = {2014}, pages = {91{\textendash}122}, abstract = {We study the problem of distributed resource sharing in peer-to-peer networks and focus on the problem of information filter- ing. In our setting, subscriptions and publications are specified using an expressive attribute-value representation that supports both the Boolean and Vector Space models. We use an extension of the distributed hash table Chord to organise the nodes and store user subscriptions, and utilise efficient publication protocols that keep the network traffic and latency low at filtering time. To verify our approach, we evaluate the proposed protocols experimentally using thousands of nodes, millions of user subscriptions, and two different real-life corpora. We also study three important facets of the load-balancing problem in such a scenario and present a novel algorithm that manages to distribute the load evenly among the nodes. Our results show that the designed protocols are scalable and efficient: they achieve expressive information filtering functionality with low message traffic and latency.}, keywords = {distributed hash tables, Information management, publish/subscribe}, author = {Christos Tryfonopoulos and Stratos Idreos and Manolis Koubarakis and Paraskevi Raftopoulou} } @conference {550, title = {DS4: A Distributed Social and Semantic Search System}, booktitle = {Proceedings of 35th European Conference on Information Retrieval (ECIR)}, year = {2013}, month = {March}, address = {Moscow, Russia}, author = {Dionisis Kontominas and Paraskevi Raftopoulou and Christos Tryfonopoulos and E.G.M. Petrakis} } @conference {539, title = {DS4: Introducing Semantic Friendship in Distributed Social Networks.}, booktitle = {Proceedings of the 21st International Conference on Cooperative Information Systems (CoopIS)}, year = {2013}, month = {September}, address = {Graz, Austria}, author = {Paraskevi Raftopoulou and Christos Tryfonopoulos and E.G.M. Petrakis and Nikos Zevlis} } @conference {594, title = {Peer Rewiring in Semantic Overlay Networks under Churn}, booktitle = {Proceedings of the 18th International Conference on Cooperative Information Systems (CoopIS)}, year = {2010}, month = {October}, publisher = {Springer-Verlag}, organization = {Springer-Verlag}, address = {Crete, Greece}, abstract = {Semantic overlay networks have been proposed as a way to organise peer-to-peer networks; peers that are semantically, thematically or socially similar are discovered and logically organised into groups. Efficient content retrieval is then performed by routing the query towards peer groups based on their likelihood to match the query. In this paper, we study the behaviour of semantic overlay networks that support full- fledged information retrieval in the presence of peer churn. We adopt a model for peer churn, and study the effect of network dynamics on peer organisation and retrieval performance. The overlay network is evaluated on a realistic peer-to-peer environment using real-world data and queries, and taking into account the dynamics of user-driven peer participation. Using this evaluation, we draw conclusions on the performance of the system in terms of clustering efficiency, communication load and retrieval accuracy in such a realistic setting.}, author = {Paraskevi Raftopoulou and E.G.M. Petrakis} } @article {540, title = {Rewiring Strategies for Semantic Overlay Networks}, journal = {Distributed and Parallel Databases (DAPD)}, volume = {26}, year = {2009}, pages = {181{\textendash}205}, abstract = {Semantic overlay networks cluster peers that are semantically, thematically or socially close into groups, by means of a rewiring procedure that is periodically executed by each peer. This procedure establishes new connections to similar peers and disregards connections to peers that are dissimilar. Retrieval effectiveness is then improved by exploiting this information at query time (as queries may address clusters of similar peers). Although all systems based on semantic overlay networks apply some rewiring technique, there is no comprehensive study showing the effect of rewiring on system{\textquoteright}s performance. In this work, a framework for studying the attribution of rewiring strategies in semantic overlay networks is proposed. A generic approach to rewiring is presented and several variants of this approach are reviewed and evaluated. We show how peer organisation is affected by the different design choices of the rewiring mechanism and how these choices affect the performance of the system overall (both in terms of communication overhead and retrieval effectiveness). Our experimental evaluation with real-word data and queries confirms the dependence between rewiring strategies and retrieval performance, and gives insights on the trade-offs involved in the selection of a rewiring strategy.}, keywords = {Information retrieval, peer-to-peer networks, rewiring strategies, semantic overlay networks}, author = {Paraskevi Raftopoulou and E.G.M. Petrakis and Christos Tryfonopoulos} } @conference {595, title = {iCluster: a Self-Organizing Overlay Network for P2P Information Retrieval}, booktitle = {Proceedings of 30th European Conference on Information Retrieval (ECIR)}, year = {2008}, month = {March}, address = {Glasgow, Scotland}, abstract = {We present iCluster, a self-organizing peer-to-peer overlay network for supporting full-fledged information retrieval in a dynamic environment. iCluster works by organizing peers sharing common interests into clusters and by exploiting clustering information at query time for achieving low network traffic and high recall. We define the criteria for peer similarity and peer selection, and we present the protocols for organizing the peers into clusters and for searching within the clustered organization of peers. iCluster is evaluated on a realistic peer-to-peer environment using real-world data and queries. The results demonstrate significant performance improvements (in terms of clustering efficiency, communication load and retrieval accuracy) over a state-of-the-art peer- to-peer clustering method. Compared to exhaustive search by flooding, iCluster exchanged a small loss in retrieval accuracy for much less message flow.}, author = {Paraskevi Raftopoulou and E.G.M. Petrakis} } @conference {549, title = {Information Retrieval and Filtering over Self-Organising Digital Libraries}, booktitle = {Proceedings of the 12th European Conference on Research and Advanced Technology for Digital Libraries (ECDL)}, year = {2008}, month = {September}, address = {Aarhus, Denmark}, author = {Paraskevi Raftopoulou and E.G.M. Petrakis and Christos Tryfonopoulos and Gerhard Weikum} } @conference {596, title = {A Measure for Cluster Cohesion in Semantic Overlay Networks}, booktitle = {Proceedings of the 6th International Workshop on Large-Scale Distributed Systems for Information Retrieval (LSDS-IR)}, year = {2008}, month = {October}, publisher = {ACM}, organization = {ACM}, address = {Napa Valley, California}, abstract = {Semantic overlay networks cluster peers that are semantically, thematically or socially close into groups by means of a rewiring procedure that is periodically executed by each peer. Rewiring proceeds by establishing new connections to similar peers, and by discarding connections that are out- dated or pointing to dissimilar peers. This process aims at improving cluster quality (how well peers with similar con- tent are clustered together) and by this, at improving the flow of information in the network by reducing the number of messages that are exchanged. Therefore, measuring the quality of clustering is an important issue by itself. This is exactly the issue this work is dealing with. In this paper, we introduce a new clustering measure that takes into account the whole neighbourhood of a peer (rather than its direct neighbours) thus, providing better insight on the quality of the underlying clustered organisation. Our experimental evaluation with real-word data and queries confirms our assumption that the new measure is better suited for measuring clustering quality than other known measures, such as the (generalised) clustering coefficient.}, author = {Paraskevi Raftopoulou and E.G.M. Petrakis} } @conference {597, title = {Design and Evaluation of Semantic Similarity Measures for Concepts Stemming from the Same or Different Ontologies}, booktitle = {Proceedings of the 4th Workshop on Multimedia Semantics (WMS)}, year = {2006}, month = {June}, address = {Chania, Crete, Greece}, abstract = {Semantic Similarity relates to computing the similarity between concepts (terms) which are not necessarily lexically similar. We investigate approaches to computing semantic similarity by mapping terms to an ontology and by examining their relationships in that ontology. More specifically, we investigate approaches to computing the semantic similarity between natural language terms (using WordNet as the underlying reference ontology) and between medical terms (using the MeSH ontology of medical and biomedical terms). The most popular semantic similarity methods are implemented and evaluated using WordNet and MeSH. The focus of this work is also on cross ontology methods which are capable of computing the semantic similarity between terms stemming from different ontologies (WordNet and MeSH in this work). This is a far more difficult problem (than the single ontology one referred to above) which has not been investigated adequately in the literature. X-Similarity, a novel cross-ontology similarity method is also a contribution of this work. All methods examined in this work are integrated into a semantic similarity system which is accessible on the Web.}, author = {E.G.M. Petrakis and Giannis Varelas and Angelos Hliaoutakis and Paraskevi Raftopoulou} } @article {592, title = {X-Similarity: Computing Semantic Similarity between Concepts from Different Ontologies}, journal = {Journal of Digital Information Management (JDIM)}, year = {2006}, month = {December}, abstract = {Semantic Similarity relates to computing the similarity between concepts (terms) which are not necessarily lexically similar. We investigate approaches to computing semantic similarity by mapping terms to an ontology and by examining their relationships in that ontology. More specifically, we investigate approaches to computing the semantic similarity between natural language terms (using WordNet as the underlying reference ontology) and between medical terms (using the MeSH ontology of medical and biomedical terms). The most popular semantic similarity methods are implemented and evaluated using WordNet and MeSH. The focus of this work is also on cross ontology methods which are capable of computing the semantic similarity between terms stemming from different ontologies (WordNet and MeSH in this work). This is a far more difficult problem (than the single ontology one referred to above) which has not been investigated adequately in the literature. X-Similarity, a novel cross-ontology similarity method is also a contribution of this work. All methods examined in this work are integrated into a semantic similarity system which is accessible on the Web.}, author = {E.G.M. Petrakis and Giannis Varelas and Angelos Hliaoutakis and Paraskevi Raftopoulou} } @article {593, title = {Fair Resource Allocation in a Simple Multi-Agent Setting: Search Algorithms and Experimental Evaluation}, journal = {International Journal on Artificial Intelligence Tools (IJAIT)}, volume = {14}, year = {2005}, month = {December}, pages = {887{\textendash}899}, abstract = {We study the problem of fair resource allocation in a simple cooperative multi-agent setting where we have k agents and a set of n objects to be allocated to those agents. Each object is associated with a weight represented by a positive integer or real number. We would like to allocate all objects to the agents so that each object is allocated to only one agent and the weight is distributed fairly. We adopt the fairness index popularized by the networking community as our measure of fairness, and study centralized algorithms for fair resource allocation. Based on the relationship between our problem and number partitioning, we devise a greedy algorithm for fair resource allocation that runs in polynomial time but is not guaranteed to find the optimal solution, and a complete anytime algorithm that finds the optimal solution but runs in exponential time. Then we study the phase transition behavior of the complete algorithm. Finally, we demonstrate that the greedy algorithm actually performs very well and returns almost perfectly fair allocations.}, keywords = {Fairness; resource allocation; number partitioning; phase transitions}, author = {Paraskevi Raftopoulou and Manolis Koubarakis and Kostas Stergiou and Peter Triantafillou} } @conference {598, title = {Semantic Similarity Methods in WordNet and their Application to Information Retrieval on the Web}, booktitle = {Proceedings of 7th ACM International Workshop on Web Information and Data Management (WIDM)}, year = {2005}, month = {November}, publisher = {ACM}, organization = {ACM}, address = {Bremen, Germany}, abstract = {Semantic Similarity relates to computing the similarity be- tween concepts which are not lexicographically similar. We investigate approaches to computing semantic similarity by mapping terms (concepts) to an ontology and by examining their relationships in that ontology. Some of the most popular semantic similarity methods are implemented and evaluated using WordNet as the underlying reference ontology. Building upon the idea of semantic similarity, a novel information retrieval method is also proposed. This method is capable of detecting similarities between documents containing semantically similar but not necessarily lexicographically similar terms. The proposed method has been evaluated in retrieval of images and documents on the Web. The experimental results demonstrated very promising performance improvements over state-of-the-art information retrieval methods.}, keywords = {Information retrieval, Semantic Similarity, WordNet, World Wide Web}, author = {Giannis Varelas and Epimenides Voutsakis and Paraskevi Raftopoulou and E.G.M. Petrakis and Evangelos Milios} } @conference {536, title = {Data Models and Languages for Agent-Based Textual Information Dissemination}, booktitle = {Proceedings of the 6th International Workshop on Cooperative Information Agents (CIA)}, year = {2002}, month = {September}, publisher = {Springer}, organization = {Springer}, address = {Madrid, Spain}, author = {Manolis Koubarakis and Christos Tryfonopoulos and Paraskevi Raftopoulou and Theodoros Koutris} } @conference {572, title = {Efficient Agent-Based Dissemination of Textual Information}, booktitle = {Proceedings of the 2nd Hellenic Conference on Artificial Intelligence (SETN)}, year = {2002}, month = {April}, address = {Thessaloniki, Greece}, author = {Manolis Koubarakis and Theodoros Koutris and Paraskevi Raftopoulou and Christos Tryfonopoulos} } @conference {546, title = {Information Alert in Distributed Digital Libraries: The Models, Languages, and Architecture of DIAS}, booktitle = {Proceedings of the 6th European Conference on Research and Advanced Technology for Digital Libraries (ECDL)}, year = {2002}, month = {September}, address = {Rome, Italy}, author = {Manolis Koubarakis and Theodoros Koutris and Christos Tryfonopoulos and Paraskevi Raftopoulou} } @conference {599, title = {Agents in Decentralised Information Ecosystems: The DIET Approach}, booktitle = {Symposium on Information Agents for E-Commerce, AISB Convention}, year = {2001}, month = {March}, address = {University of York, United Kingdom}, abstract = {The complexity of the current global information infrastructure requires novel means of understanding and exploiting the dynamics of information. One means may be through the concept of an information ecosystem. An information ecosystem is analogous to a natural ecosystem in which there are flows of materials and energy analogous to information flow between many interacting individuals. This paper describes a multi-agent platform, DIET (Decentralised Information Ecosystem Technologies) that can be used to implement open, robust, adaptive and scalable ecosystem-inspired systems. We describe the design principles of the DIET software architecture, and present a simple example application based upon it. We go on to consider how the DIET system can be used to develop information brokering agents, and how these can contribute to the implementation of economic interactions between agents, as well as identifying some open questions relating to research in these areas. In this way we show the capacity of the DIET system to support applications using information agents.}, author = {P. Marrow and Manolis Koubarakis and R.H. van Lengen and F. Valverde-Albacete and E. Bonsma and J. Cid-Suerio and A.R. Figueiras-Vidal and A. Gallardo-Antolin and C. Hoile and T. Koutris and H. Molina-Bulla and A. Navia-Vazquez and Paraskevi Raftopoulou and N. Skarmeas and Christos Tryfonopoulos and F. Wang and C. Xiruhaki} } @conference {aisb01-MKL+, title = {Agents in Decentralised Information Ecosystems: The DIET Approach}, booktitle = {Proccedings of the Symposium on Information Agents for E-Commerce, AISB Convention}, year = {2001}, month = {March}, pages = {109{\textendash}117}, address = {York, UK}, author = {P. Marrow and Manolis Koubarakis and R.H. van Lengen and F. Valverde-Albacete and E. Bonsma and J. Cid-Suerio and A.R. Figueiras-Vidal and A. Gallardo-Antolin and C. Hoile and T. Koutris and H. Molina-Bulla and A. Navia-Vazquez and Paraskevi Raftopoulou and N. Skarmeas and Christos Tryfonopoulos and F. Wang and C. Xiruhaki} }