Pericles A. Mitkas

Aristotle University of Thessaloniki | AUTH · Department of Electronics and Computer Engineering

Nowadays, the fashion clothing industry is moving towards “fast” fashion, offering a wide variety of products based on different patterns and styles, usually characterized by lower costs and ambiguous quality. The retails markets are trying to present regularly new fashion collections while trying to follow the latest fashion trends at the same tim...

In the clothing industry, design, development, and procurement teams have been affected more than any other industry and are constantly under pressure to present more products with fewer resources in a shorter time. The diversity of garment designs created as new products is not found in any other industry and is almost independent of the size of t...

Background Antigen receptors are characterized by an extreme diversity of specificities, which poses major computational and analytical challenges, particularly in the era of high-throughput immunoprofiling by next generation sequencing (NGS). The T cell Receptor/Immunoglobulin Profiler (TRIP) tool offers the opportunity for an in-depth analysis ba...

Nowadays, the fashion industry is moving towards fast fashion, offering a large selection of garment products in a quicker and cheaper manner. To this end, the fashion designers are required to come up with a wide and diverse amount of fashion products in a short time frame. At the same time, the fashion retailers are oriented towards using technol...

Scalable big data analysis frameworks are of paramount importance in the modern web society, which is characterized by a huge number of resources, including electronic text documents. Document clustering is an important field in text mining and is commonly used for document organization, browsing, summarization and classification. Hierarchical clus...

Nowadays, a wide range of sciences are moving towards the Big Data era, producing large volumes of data that require processing for new knowledge extraction. Scientific workflows are often the key tools for solving problems characterized by computational complexity and data diversity, whereas cloud computing can effectively facilitate their efficie...

Any computational process from simple data analytics tasks to training a machine learning model can be described by a workflow. Many workflow management systems (WMS) exist that undertake the task of scheduling workflows across distributed computational resources. In this work, we introduce a WMS that leverages machine learning to predict workflow...

Hyper-personalization intends to maximize the opportunities a marketer has to tailor content that fits each and every customer’s wants and needs. Naturally, gathering and analyzing more data is the key to those opportunities. This is were the “Conversation Web” comes in, which in the near future is expected to transform to so much more than just co...

An important problem in the live music industry is finding venues that help expose artists to wider audiences. However, it is often difficult to obtain live music audience data to tackle this task. In this work, we investigate whether important venues can instead be inferred through social media data. Our approach consists of employing bipartite gr...

In the recent years, we have witnessed the rapid adoption of social media platforms, such as Twitter, Facebook and YouTube, and their use as part of the everyday life of billions of people worldwide. Given the habit of people to use these platforms to share thoughts, daily activities and experiences it is not surprising that the amount of user gene...

Recent developments in deep reinforcement learning have enabled the creation of agents for solving a large variety of games given a visual input. These methods have been proven successful for 2D games, like the Atari games, or for simple tasks, like navigating in mazes. It is still an open question, how to address more complex environments, in whic...

The identification of meaningful groups of proteins has always been a major area of interest for structural and functional genomics. Successful protein clustering can lead to significant insight, assisting in both tracing the evolutionary history of the respective molecules as well as in identifying potential functions and interactions of novel seq...

Hermes introduces a new ”describe once, run anywhere” paradigm for the execution of bioinformatics workflows in hybrid cloud environments. It combines the traditional features of parallelization-enabled workflow management systems and of distributed computing platforms in a container-based approach. It offers seamless deployment, overcoming the bur...

Nowadays, the construction of a complex robotic system requires a high level of specialization in a large number of diverse scientific areas. It is reasonable that a single researcher cannot create from scratch the entirety of this system, as it is impossible for him to have the necessary skills in the necessary fields. This obstacle is being surpa...

The paper describes a technical demonstration of an open-source framework for monitoring, analysis and search over multiple social media platforms. The framework is intended to be a valuable tool for media intelligence professionals, as well as a framework and testbed for scientists and developers with interest in social media research.

Contemporary electricity markets necessitate balancing supply and demand in real time, as well as the active involvement of all participating entities in the price-setting procedure. To this end, Demand Response pricing schemes are often introduced, encouraging customers to contribute to power system stability by reducing their load during peak per...

This paper presents a method of designing variable structure control systems for robots. As the on-board robot computational resources are limited, but in some cases the demands imposed on the robot by the user are virtually limitless, the solution is to produce a variable structure system. The task dependent part has to be exchanged, however the t...

Life Sciences have been established and widely accepted as a foremost Big Data discipline; as such they are a constant source of the most computationally challenging problems. In order to provide efficient solutions, the community is turning towards scalable approaches such as the utilization of cloud resources in addition to any existing local com...

Current research in Life Sciences without doubt has been established as a Big Data discipline. Beyond the expected domain-specific requirements, this perspective has put scalability as one of the most crucial aspects of any state-of-the-art bioinformatics framework. Sequence alignment and construction of phylogenetic profiles are common tasks evide...

Scientific breakthroughs have led to an increase in life expectancy, to the point where senior citizens comprise an ever increasing percentage of the general population. In this direction, the EU funded RAPP project “Robotic Applications for Delivering Smart User Empowering Applications” introduces socially interactive robots that will not only phy...

Social robotics have become a trend in contemporary robotics research since they can be successfully used in a wide range of applications. One of the most fundamental communication skills a consumer robot must have is the oral interaction with a human in order to provide feedback or accept commands. There are quite a few well established Automatic...

It is a general truth that increase of age is associated with a level of mental and physical decline but unfortunately the former are often accompanied by social exclusion leading to marginalization and eventually further acceleration of the aging process. A new approach in alleviating the social exclusion of older people involves the use of assist...

This paper describes a multimodal graph-based approach to address the problem of event detection and summarization in large scale image collections. A first version of our system was presented in the Yahoo-Flickr Event Summarization Challenge of ACM Multimedia 2015 [6]. The objective of the approach is to automatically detect events within millions...

Due to the increasing popularity of social media platforms, the amount of messages (posts) related to public events, especially posts sharing multimedia content, is steadily increasing. Sharing images can contribute to a rich and live coverage of the event. Yet, despite the value and interestingness of some posts, there is a lot of spam and redunda...

In recent years, multi-label classification has attracted a significant body of research, motivated by real-life applications, such as text classification and medical diagnoses. Although sparsely studied in this context, Learning Classifier Systems are naturally well-suited to multi-label classification problems, whose search space typically involv...

Medical advances have increased life expectancy to the point where senior citizens comprise a larger than ever percentage of the general population. The RAPP project introduces socially interactive robots that will not only physically assist, but also serve as a companion to senior citizens. In this paper, a novel system is presented, designed as p...

The paper describes a multimodal graph-based system for addressing the Yahoo-Flickr Event Summarization Challenge of ACM Multimedia 2015. The objective is to automatically uncover structure within a collection of 100 million photos/videos in the form of detecting and identifying events, and summarizing them succinctly for consumer consumption. The...

Social robotics have become a trend in contemporary robotics research, since they can be successfully used in a wide range of applications. One of the most fundamental communication skills a robot must have is the oral interaction with a human, in order to provide feedback or accept commands. And, although text-to-speech is an almost solved problem...

Energy gives personal comfort to people, and is essential for the generation of commercial and societal wealth. Nevertheless, energy production and consumption place considerable pressures on the environment, such as the emission of green- house gases and air pollutants. They contribute to climate change, damage natural ecosystems and the man-made...

Due to the increasing popularity of microblogging platforms, the amount of messages (posts) related to public events, especially posts encompassing multimedia content, is steadily increasing. The inclusion of images can convey much more information about the event, compared to their text, which is typically very short (e.g., tweets). Although such...

Despite the plethora of frameworks and tools for developing agent systems, there is a remarkable lack of generalised methodologies for assessing their performance. Existing methods in the field of software engineering do not adequately address the unpredictable and complex nature of intelligent agents. We introduce a generic methodology for evaluat...

Short-Term Load and Price forecasting are crucial to the stability of electricity markets and to the profitability of the involved parties. The work presented here makes use of a Local Linear Wavelet Neural Network (LLWNN) trained by a special adaptive version of the Particle Swarm Optimization algorithm and implemented as parallel process in CUDA....

In the wake of gene-oriented data analysis in large-scale bioinformatics studies, focus in research is currently shifting towards the analysis of the functional association of genes, namely the metabolic pathways in which genes participate. The goal of this paper is to attempt to identify the core genes in a specific pathway, based on a user-define...

As our societies are affected by a dramatic demographic change, the percentage of elderly and people requiring support in their daily life is expected to increase in the near future and caregivers will not be enough to assist and support them. Socially interactive robots can help confront this situation not only by physically assisting people but a...

The recent advent of Cloud Computing, inevitably gave rise to Cloud Robotics. Whilst the field is arguably still in its infancy, great promise is shown regarding the problem of limited computational power in Robotics. This is the most evident advantage of Cloud Robotics, but, other much more significant yet subtle advantages can now be identified....

Cloud robotics is becoming a trend in the modern robotics field, as it became evident that true artificial intelligence can be achieved only by sharing collective knowledge. In the ICT area, the most common way to formulate knowledge is via the ontology concept, where different meanings connect semantically. Additionally, a considerable effort to m...

In the era of Big Data in Life Sciences, efficient processing and analysis of vast amounts of sequence data is becoming an ever daunting challenge. Among such analyses, sequence alignment is one of the most commonly used procedures, as it provides useful insights on the functionality and relationship of the involved entities. Sequence alignment is...

The main challenge of the Smart Grid Paradigm is achieving a tight balance between supply and demand of electrical energy. A contemporary approach to address this challenge is the use of autonomous broker agents. These intelligent entities are able to interact with both producers and consumers by offering tariffs, in order to buy or sell energy, re...

In contemporary power systems, small-scale consumers account for up to 50% of a country׳s total electrical energy consumption. Nevertheless, not much has been achieved towards eliminating the problems caused by their inelastic consumption habits, namely the peaks in their daily power demand and the inability of energy suppliers to perform short-ter...

The identification of meaningful groups of proteins has always been a principal goal in structural and functional genomics. A successful protein clustering can lead to significant insight, both in the evolutionary history of the respective molecules and in the identification of potential functions and interactions of novel sequences. In this work w...

Due to the increasing popularity of microblog- ging platforms, the amount of messages re- lated to large scale public events reach impres- sive levels. Although such messages can be quite informative regarding different aspects of the main event, there is a lot of spam and re- dundancy that makes it challenging to extract insights regarding the eve...

In contemporary power systems, residential consumers may account for up to 50% of a country's total electrical energy consumption. Even though they constitute a significant portion of the energy market, not much has been achieved towards eliminating the inability for energy suppliers to perform long-term portfolio management, thus maximizing their...

The problem of identifying important online or real life events from large textual document streams that are freely available on the World Wide Web is increasingly gaining popularity, given the flourishing of the social web. An event triggers discussion and comments on the WWW, especially in the blogosphere and in microblogging services. Consequent...

Energy markets have undergone important changes at the conceptual level over the last years. Decentralized supply, small-scale production and smart grid optimization and control are the new building blocks. These changes offer substantial opportunities for all energy market stakeholders, some of which however, remain largely unexploited. Small-scal...

In this paper we present a research system that follows a semantic approach to facilitate medical association studies in the area of cervical cancer. Our system, named ASSIST and developed as an EU research project, assists in cervical cancer research by unifying multiple patient record repositories, physically located in different medical centers...

In recent years, multi-label classification has attracted a significant body of research, motivated by real-life applications such as text classification and medical diagnoses. However, rule-based methods, and especially Learning Classifier Systems (LCS), for tackling such problems have only been sparsely studied. This is the motivation behind our...

The development of real-world, fully autonomous agents would require mechanisms that would offer generalization capabilities from experience, suitable for a large range of machine learning tasks, like those from the areas of supervised and reinforcement learning. Such capacities could be offered by parametric function approximators that could eithe...

Learning classifier systems (LCS) are machine learning systems designed to work for both multi-step and single-step decision tasks. The latter case presents an interesting challenge for such algorithms, especially when they are applied to real-world data mining (DM) problems. The present investigation departs from the popular approach of applying a...

Phylogenetic profiles express the presence or absence of genes and their homologs across a number of reference genomes. They have emerged as an elegant representation framework for comparative genomics and have been used for the genome-wide inference and discovery of functionally linked genes or metabolic pathways. As the number of reference genome...

Software. Software application and documentation. (GZ)

Search for optimal parameters. Optimization of parameter values for parameters α, λ and distance metric. (PDF)

Full tree of five reference species. Full tree of five reference species. (BMP)

Agent autonomy is strongly related to learning and adap-tation. Machine learning models generated, either by off-line or on-line adaptation, through the use of historical data or current environmental signals, provide agents with the necessary decision-making and gener-alization capabilities in competitive, dynamic, partially observable and stochas...

Sponsored search auctions constitutes the most im-portant source of revenue for search engine com-panies, offering new opportunities for advertisers. The Trading Agent Competition (TAC) Ad Auc-tions tournament is one of the first attempts to study the competition among advertisers for their place-ment in sponsored positions along with organic searc...

The emergence of Multi-Agent systems as a software paradigm that most suitably fits all types of problems and architectures is already experiencing significant revisions. A more consistent approach on agent programming, and the adoption of Software Engineering standards has indicated the pros and cons of Agent Technology and has limited the scope o...

The rationalization of electrical energy consumption is a constant goal driving research over the last decades. The pursuit of efficient solutions requires the involvement of electrical energy consumers through Demand Response programs. In this study, a framework is presented that can serve as a tool for designing and simulating Demand Response pro...

In the wake of gene-oriented data analysis in large-scale bioinformatics studies, focus in research is currently shifting towards the analysis of the functional association of genes, namely the metabolic pathways in which genes participate. The goal of this paper is to attempt to identify the core genes in a specific pathway, based on a user-define...

This paper discusses the design and implementation of a highly efficient MiniMax algorithm for the game Abalone. For perfect information games with relatively low branching factor for their decision tree (such as Chess, Checkers etc.) and a highly accurate evaluation function, Alpha-Beta search proved to be far more efficient than Monte Carlo Tree...

The present paper investigates whether an “informed” initialization process can help supervised LCS algorithms evolve rulesets with better characteristics, including greater predictive accuracy, shorter training times, and/or more compact knowledge representations. Inspired by previous research suggesting that the initialization phase of evolutiona...

This paper presents WebOWL, an experiment in using the latest technologies to develop a Semantic Web search engine. WebOWL consists of a community of intelligent agents, acting as crawlers, that are able to discover and learn the locations of Semantic Web neighborhoods on the Web, a semantic database to store data from different ontologies, a query...

The scope of this chapter is the presentation of Data Mining techniques for knowledge extraction in proteomics, taking into account both the particular features of most proteomics issues (such as data retrieval and system complexity), and the opportunities and constraints found in a Grid environment. The chapter discusses the way new and potentiall...

In this work we focus on folksonomies. Our goal is to develop techniques that coordinate information processing, by taking advantage of user preferences, in order to automatically produce semantic tag recommendations. To this end, we propose a generalized tag recommendation framework that conveys the semantics of resources according to different us...

The analysis of completely sequenced genomes can yield useful insight into the evolution and multi-level organization of organisms. From the lowest level of molecular organization where individual enzymes are formed, to the higher level, where sets of enzymes group into metabolic networks, the effects of gene evolution can be detected. With the cur...

The major goal of transfer learning is to transfer knowledge acquired on a source task in order to facilitate learning on another, different, but usually related, target task. In this paper, we are using neuroevolution to evolve echo state networks on the source task and transfer the best performing reservoirs to be used as initial population on th...

The prediction of gene function from genome sequences is one of the main issues in Bioinformatics. Most computational approaches are based on the similarity between sequences to infer gene function. However, the availability of several fully sequenced genomes has enabled alternative approaches, such as phylogenetic profiles. Phylogenetic profiles a...

Real Time Strategy games (RTS) provide an inter- esting test bed for agents that use Reinforcement Learning (RL) algorithms. From an agent's point of view, RTS games constitute a Markovian, partially observable and dynamic environment with a huge state space. In this paper, we present an agent that uses a Zeroth-level Classifier System (ZCS) in ord...

In this paper we analyze and compare three popular content creation and sharing websites, namely Panoramio, YouTube and Epinions. This analysis aims in advancing our understanding of Web Social Media and their impact, and may be useful in creating feedback mechanisms for increasing user participation and sharing. For each of the three websites, we...

In recent years, Time Series Prediction and clustering have been employed in hyperactive and evolving environments –where temporal data play an important role– as a result of the need for reliable methods to estimate and predict the pattern or behavior of events and systems. Power Stock Markets are such highly dynamic and competitive auction enviro...

Sparse episode identification in environmental datasets is not only a multi-faceted and computationally challenging problem for machine learning algorithms, but also a difficult task for human-decision makers: the strict regulatory framework, in combination with the public demand for better information services, poses the need for robust, efficient...

This work discusses the quantification of specialization in a multi-agent system as an evaluation metric. There is currently no commonly accepted evaluation methodology for multi-agent systems and their complexity emphasizes the need to quantify high-level abstract evaluation metrics. Based on previous work, we measure specialization in two dimensi...

TAC Market Design (or CAT) tournament is an effort to study the competition among modern stock exchanges trying to at- tract potential traders while maximizing their profit. This paper shortly presents Mertacor, our entrant for 2008, and makes an attempt to evaluate its performance. We compare Mertacor with the other available entries for the setti...

The transition from the traditional to the Semantic Web has proven much more difficult than initially expected. The volume, complexity and versatility of data of various domains, the computational limitations imposed on semantic querying and inferencing have drastically reduced the thrust semantic technologies had when initially introduced. In orde...

The annual Trading Agent Competition for Market Design, cat, provides a testbed to study the mechanisms that modern stock exchanges use in their effort to attract potential traders while maximizing their profit. This paper presents an evaluation of the agents that participated in the 2008 competition. The evaluation is based on the analysis of the...

Real-time systems can be defined as systems operating under specific timing constraints, either hard or soft ones. In principle, agent systems are considered inappropriate for such kinds of systems, due to the asynchronous nature of their communication protocols, which directly influences their temporal behavior. Nevertheless, multi-agent systems c...

Web 2.0 provided internet users with a dynamic medium, where information is updated continuously and anyone can participate. Though preliminary analysis exists, there is still little understanding on what exactly stimulates users to actively participate, create and share content in online communities. In this paper we present a methodology that asp...

A Grid environment can be viewed as a virtual computing architecture that provides the ability to perform higher throughput computing by taking advantage of many computers geographically dispersed and connected by a network. Bioinformatics applications stand to gain in such a distributed environment in terms of increased availability, reliability a...

Current global economy involves highly interconnected markets competing with each other for market share and profit. The recent global financial crisis has revived research interest in this competition and has brought out the need for novel, efficient rules. TAC Market Design tournament is one of the first efforts in studying the interaction betwee...

The Reinforcement Learning (RL) paradigm is an appropriate formulation for agent, goal-directed, sequential decision making. In order though for RL methods to perform well in difficult, complex, real-world tasks, the choice and the architecture of an appropriate function approximator is of crucial importance. This work presents a method of automati...

The prediction of gene function from genome sequences is one of the main issues in Bioinformatics. Most computational approaches are based on the similarity between sequences to infer gene function. However, the availability of several fully sequenced genomes has enabled alternative approaches, such as phylogenetic profiles. Phylogenetic profiles a...

During the last decade, there has been intense research and development in creating methodologies and tools able to map Relational Databases with the Resource Description Framework. Although some systems have gained wider acceptance in the Semantic Web community, they either require users to learn a declarative language for encoding mappings, or ha...

This chapter discusses the current state-of-the-art of agents and multi-agent systems (MAS) in supply chain management (SCM). Following a general description of SCM and the challenges it is currently ed with we present MAS as a possible solution to these challenge. We argue that an application involving multiple autonomous actors, such as SCM, can...

The complex structure of semantic data still poses a challenge in storing, querying, and organizing Web information. Although researchers have proposed various semantic database system approaches over the years, it seems that most systems have tried to provide industrial-strength scalability too soon. Consequently, most semantic databases still rel...

The continuous processing and evaluation of meteorological radar data require significant efforts by scientists, both for data processing, storage, and maintenance, and for data interpretation and visualization. To assist meteorologists and to automate a large part of these tasks, we have designed and developed Abacus, a multi-agent system for mana...