
Dimitris PlexousakisUniversity of Crete | UOC · Department of Computer Science
Dimitris Plexousakis
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Publications
Publications (277)
Digital innovation can significantly enhance public health services, environmental sustainability, and social welfare. To this end, the European Digital Innovation Hub (EDIH) initiative was funded by the European Commission and national governments aiming to facilitate the digital transformation on various domains (including health) via the setup o...
The European Digital Innovation Hub for Smart Health: Precision Medicine and Innovative eHealth Services (smartHEALTH) is a strategic partnership between the most significant research and academic institutions, as well as representatives from the private sector in Greece. The goal of smartHEALTH is to create and operate a one-stop shop for providin...
Anticipating object state changes in images and videos is a challenging problem whose solution has important implications in vision-based scene understanding, automated monitoring systems, and action planning. In this work, we propose the first method for solving this problem. The proposed method predicts object state changes that will occur in the...
Domain-specific knowledge can significantly contribute to addressing a wide variety of vision tasks. However, the generation of such knowledge entails considerable human labor and time costs. This study investigates the potential of Large Language Models (LLMs) in generating and providing domain-specific information through semantic embeddings. To...
The explosion of the web and the abundance of linked data demand effective and efficient methods for storage, management, and querying. Apache Spark is one of the most widely used engines for big data processing, with more and more systems adopting it for efficient query answering. Existing approaches exploiting Spark for querying RDF data, adopt p...
Named Entity Recognition (NER) and Linking (NEL) have seen great advances lately, especially with the development of language models pre-trained on large document corpora, typically written in the most popular languages (e.g., English). This makes NER and NEL tools for other languages, with fewer resources available, fall behind the latest advances...
We investigate the problem of Object State Classification (OSC) as a zero-shot learning problem. Specifically, we propose the first Object-agnostic State Classification (OaSC) method that infers the state of a certain object without relying on the knowledge or the estimation of the object class. In that direction, we capitalize on Knowledge Graphs...
The exchange of comments, opinions, and arguments in blogs, forums, social media, wikis, and review websites has transformed the Web into a modern agora, a virtual place where all types of debates take place. This wealth of information remains mostly unexploited: due to its textual form, such information is difficult to automatically process and an...
argumentation frameworks (AAFs), introduced by Dung (1995, Artif. Intell., 228, 321–357), enabled a new way of reasoning with arguments, which does not take into account the internal structure of arguments but only how they are related to each other. The only form of relation considered in AAFs is a binary attack relation on the set of arguments. F...
This paper presents a model-based approach to facilitate the development of IoT applications in Transportation Systems. Existing public transportation services are provided by relying on standard data models such as GTFS. However, such models are limited in representing IoT-based infrastructures and the locations that IoT devices cover (e.g., bus s...
More and more weakly structured, and irregular data sources are becoming available every day. The schema of these sources is useful for a number of tasks, such as query answering, exploration and summarization. However, although semantic web data might contain schema information, in many cases this is completely missing or partially defined. In thi...
Reasoning about actions, change, and causality constitutes an important field of research in artificial intelligence. Several formal action languages have been proposed, addressing the need to qualify change and facilitate (commonsense) reasoning in dynamic settings. The Event Calculus (EC), in particular, permits the representation of causal and n...
The detection of object states in images (State Detection - SD) is a problem of both theoretical and practical importance and it is tightly interwoven with other important computer vision problems, such as action recognition and affordance detection. It is also highly relevant to any entity that needs to reason and act in dynamic domains, such as r...
In this work we consider the collection of deceptive April Fools' Day(AFD) news articles as a useful addition in existing datasets for deception detection tasks. Such collections have an established ground truth and are relatively easy to construct across languages. As a result, we introduce a corpus that includes diachronic AFD and normal articles...
This paper presents a novel abstract argumentation framework, called Multi-Attack Argumentation Framework (MAAF), which supports different types of attacks. The introduction of types gives rise to a new family of non-standard semantics which can support applications that classical approaches cannot, while also allowing classical semantics as a spec...
Infusing autonomous artificial systems with knowledge about the physical world they inhabit is of utmost importance and a long-lasting goal in Artificial Intelligence (AI) research. Training systems with relevant data is a common approach; yet, it is not always feasible to find the data needed, especially since a big portion of this knowledge is co...
Argumentative discourse rarely consists of opinions whose claims apply universally. As with logical statements, an argument applies to specific objects in the universe or relations among them, and may have exceptions. In this paper, we propose an argumentation formalism that allows associating arguments with a domain of application. Appropriate sem...
Automatic deception detection is a crucial task that has many applications both in direct physical and in computer-mediated human communication. Our focus is on automatic deception detection in text across cultures. In this context, we view culture through the prism of the individualism/collectivism dimension, and we approximate culture by using co...
Deception detection is a task with many applications both in direct physical and in computer-mediated communication. Our focus is on automatic deception detection in text across cultures. We view culture through the prism of the individualism/collectivism dimension and we approximate culture by using country as a proxy. Having as a starting point r...
HIFUN is a high-level query language for expressing analytic queries of big datasets, offering a clear separation between the conceptual layer, where analytic queries are defined independently of the nature and location of data, and the physical layer, where queries are evaluated. In this paper, we present a methodology based on the HIFUN language,...
Telos is a conceptual modeling language intended to capture software knowledge, such as software system requirements, domain knowledge, architectures, design decisions and more. To accomplish this, Telos was designed to be extensible in the sense that the concepts used to capture software knowledge can be defined in the language itself, instead of...
Recent extensions of the Event Calculus resulted in powerful formalisms, able to reason about a multitude of commonsense phenomena in causal domains, involving epistemic notions, functional fluents and probabilistic aspects, among others. Less attention has been paid to the problem of automatically revising (correcting) a Knowledge Base when an obs...
Abstract Background The long-term outcome of rheumatoid arthritis (RA) patients who in clinical practice exhibit persistent moderate disease activity (pMDA) despite treatment with biologics has not been adequately studied. Herein, we analyzed the 5-year outcome of the pMDA group and assessed for within-group heterogeneity. Methods We included longi...
The field of Computational Argumentation is well-tailored to approach commonsense reasoning, due to its ability to model contradictory information. In this paper, we present preliminary work on how an argumentation framework can explicitly model commonsense knowledge, both at a logically structured and at an abstract level. We discuss the correlati...
Background The long-term outcome of rheumatoid arthritis (RA) patients who in clinical practice, exhibit persistent moderate disease activity (pMDA) despite treatment with biologics has not been adequately studied. Herein, we analyzed the 5-year outcome of the pMDA group and assessed for within-group heterogeneity.
Methods We included longitudinal...
Background The long-term outcome of rheumatoid arthritis (RA) patients who in clinical practice exhibit persistent moderate disease activity (pMDA) despite treatment with biologics has not been adequately studied. Herein, we analyzed the 5-year outcome of the pMDA group and assessed for within-group heterogeneity.
Methods We included longitudinall...
We proposed the European Laboratory for Gravitation and Atom-interferometric Research (ELGAR), an array of atom gradiometers aimed at studying space-time and gravitation with the primary goal of observing gravitational waves (GWs) in the infrasound band with a peak strain sensitivity of $3.3 \times 10^{-22}/\sqrt{\text{Hz}}$ at 1.7 Hz. In this pape...
Cloud computing is the most prevailing computing paradigm as it has led to a proliferation of cloud-based applications, either through the migration of existing legacy or the development of novel ones from scratch. In fact, nowadays, there is also a move towards adopting multi-clouds due to the main benefits they introduce, including vendor lock-in...
A huge amount of data is generated each day from various sources. Analysis of these massive data is difficult, and requires new forms of processing to enable enhanced decision making, insight discovery and process optimization. In addition, besides their ever increasing volume, datasets change frequently, and as such, results to continuous queries...
This book constitutes the revised selected papers of the 13th International Workshop on Information Search, Integration and Personalization, ISIP 2019, held in Heraklion, Greece, in May 2019.
The volume presents 11 revised full papers, which were carefully reviewed and selected from 16 papers submitted to these post-conference proceedings. The pap...
Object perception is a fundamental sub-field of Computer Vision, covering a multitude of individual areas and having contributed high-impact results. While Machine Learning has been traditionally applied to address related problems, recent works also seek ways to integrate knowledge engineering in order to expand the level of intelligence of the vi...
ECAVI (Event Calculus Analysis and VIsualisation), is a domain independent visual modelling tool for designing dynamic domains in the Event Calculus. ECAVI is mainly addressed to inexperienced modellers,
aiming to acquaint them with the features of the Event Calculus (and consequently commonsense reasoning) and to guide them during the process of d...
Gravitational Waves (GWs) were observed for the first time in 2015, one century after Einstein predicted their existence. There is now growing interest to extend the detection bandwidth to low frequency. The scientific potential of multi-frequency GW astronomy is enormous as it would enable to obtain a more complete picture of cosmic events and mec...
Over the last few years, we witness an explosion on the development of data management solutions for big data applications. To this direction, NoSQL databases provide new opportunities by enabling elastic scaling, fault tolerance, high availability and schema flexibility. Despite these benefits, their limitations in the flexibility of query mechani...
In this paper, we present RDFDigest+, a novel tool that enables effective and efficient RDF/S Knowledge Base (KB) exploration using summaries. The tool employs a diverse set of algorithms for identifying the most important nodes, offering a wide range of possibilities to capture importance. The selected nodes can be combined using multiple state of...
In clinical practice, approximately 50% of RA patients on bDMARDs have persistent moderate disease activity (pMDA) in spite of bDMARDs switches. Although patients on pMDA present early significant improvement in HAQ, they still have worse functional status, compared to patients in persistent low disease activity or remission, after 3 years of follo...
This paper describes the implementation of an Internet of Things (IoT) and Open Data infrastructure by the Institute of Computer Science of the Foundation for Research and Technology - Hellas (FORTH-ICS) for the city of Heraklion, focusing on the application of mature research and development outcomes in a Smart City context. These outcomes mainly...
Significant efforts have been dedicated recently to the development of architectures for storing and querying RDF data in distributed environments. Several approaches focus on data partitioning, which are able to answer queries efficiently, by using a small number of computational nodes. However, such approaches provide static data partitions. Give...
Linked Data (LD) technology enables integrating information across disparate sources and can be exploited to perform inferencing for deriving added-value knowledge. As such, it can really support performing different kinds of analysis tasks over business process (BP) execution related information. When moving BPs in the cloud, giving rise to Busine...
Significant efforts have been dedicated recently to the development of architectures for storing and querying RDF data in distributed environments. Several approaches focus on data partitioning, which are able to answer queries efficiently, by using a small number of computational nodes. However, such approaches provide static data partitions. Give...
The goal of our research has been to integrate existing information systems and to design and implement a prototype of a digital personal travel assistant for travelers, called Travel Companion. Travel Companion assists a traveler through various guidance functions, and offers personalized reminders and recommendations, which are based on the trave...
The explosion of the web and the abundance of linked data demand for effective and efficient methods for storage, management and querying. More specifically, the ever-increasing size and number of RDF data collections raises the need for efficient query answering, and dictates the usage of distributed data management systems for effectively partiti...
Modern service-based applications (SBAs) operate in highly dynamic environments where both underlying resources and the application demand can be constantly changing which external SBA components might fail. Thus, they need to be rapidly modified to address such changes. Such a rapid updating should be performed across multiple levels to better dea...
User reviews, comments and votes on the Social Web form the modern version of word-of-mouth communication, which has a huge impact on people’s shopping habits, businesses and the overall market. Despite that, systems have so far limited practical success in helping consumers and businesses analysing, managing and understanding Social Web content. I...
A vast amount of opinions are surfacing on the Web but the lack of mechanisms for managing them leads to confusing and often chaotic dialogues. This creates the need for further semantic infrastructure and analysis of the views expressed in large-volume discussions. In this paper, we describe a web platform for modeling and analyzing argumentative...
In this work we discuss the related challenges and describe an approach towards the fusion of state-of-the-art technologies from the Spoken Dialogue Systems (SDS) and the Semantic Web and Information Retrieval domains. We envision a dialogue system named LD-SDS that will support advanced, expressive, and engaging user requests, over multiple, compl...
Today we are witnessing an explosion in the size and the amount of the available RDF datasets. As such, conventional single node RDF management systems give their position to clustered ones. However most of the currently available clustered RDF database systems partition data using hash functions and/or vertical and horizontal partition algorithms...
Effective and accurate service discovery and composition rely on complete specifications of service behaviour, containing inputs and preconditions that are required before service execution, outputs, effects and ramifications of a successful execution and explanations for unsuccessful executions. The previously defined Web Service Specification Lan...
The need to manage embedded systems, brought forward by the wider adoption of pervasive computing, is particularly vital in the context of secure and safety-critical applications. Technology infiltrates in ordinary things, hitching intelligence and materializing smart systems. Each of these individual entities monitors a specific set of parameters...
This paper presents the definition of the collective utility of groups of entities called ensembles that come into a collaboration to accomplish their individual goals. We propose an analytic method for assessing the utility of an ensemble taking into account the entities preferences. We use this model to build a hierarchy of utilities that corresp...
We introduce ArgQL, a declarative query language, which performs on a data model designed according to the principles of argumentation. Its syntax is based on Cypher (language for graph databases) and SPARQL 1.1 and is adjusted for querying dialogues, composed by sets of arguments and their interrelations. We use formal semantics to show how querie...
Given the explosive growth in the size and the complexity of the Data Web, there is now more than ever, an increasing need to develop methods and tools in order to facilitate the understanding and exploration of RDF/S Knowledge Bases (KBs). To this direction, summarization approaches try to produce an abridged version of the original data source, h...
This paper reports the re-engineering efforts for OWL-Q, a prominent semantic quality-based service description language. These efforts have focused on making OWL-Q more compact without reducing its level of expressiveness as well as enriching it with semantic rules towards semantic validation of quality specifications and new knowledge derivation....
Given the explosive growth in both data size and schema complexity, data sources are becoming increasingly difficult to use and comprehend. Summarization aspires to produce an abridged version of the original data source highlighting its most representative concepts. In this paper, we present an advanced version of the RDF Digest, a novel platform...
Service-orientation is increasingly adopted by application and service developers, leading to a plethora of services becoming increasingly available. To enable constructing applications from such services, respective service description and discovery must be supported by considering both functional and non-functional aspects as they play a signific...
Service-orientation has revolutionized the way applications are constructed and provisioned. To this end, a proliferation of web services is being increasingly available. To exploit such services, an accurate service discovery process is required with a suitable performance focusing both on functional and quality of service (QoS) aspects. In fact,...