IDEAS

This invited talk explores the research challenges in the domain of IoT from multiple angles and reflects on the urgently needed collective efforts from various research communities to collaborate on those. Our approach fundamentally challenges the ...

We often add arithmetic to extend the expressiveness of query languages, tuple generating dependencies and data exchange mappings, and study the complexity of problems such as testing query containment and finding certain answers. When adding arithmetic ...

During the last few decades the problem of community detection in social networks has become an important and challenging computational task. Consequently, a number of algorithms have been proposed in the relevant literature, some of which seem to solve ...

Crime has been prevalent in our society for a very long time and it continues to be so even today. Currently, many cities have released crime-related data as part of an open data initiative. Using this as input, we can apply analytics to be able to ...

The classification of electroencephalography (EEG) signals is useful in a wide range of applications such as seizure detection/prediction, motor imagery classification, emotion classification and drug effects diagnosis, amongst others. With the large ...

Data publishing is a challenging task from the privacy point of view. Different anonymization techniques are proposed in the literature to preserve privacy in accordance with some mathematical constraints. Disassociation is one of the anonymization ...

Recent advances in sensor technology and information processing have allowed connected environments to impact various application domains. In order to detect events in these environments, existing works rely on the sensed data. However, these works are ...

Semantic web techniques (e.g., ontologies) have been recently adopted for sensor network modeling. However, existing works do not fully address these challenges: (i) representing different sensor types (e.g., mobile/static sensors) to enrich the network ...

Web of Trust offers a way to bind identities with the corresponding public keys. It relies on a distributed architecture, where each user could play the role of certificate signer. With the widespread diffusion of social networks, the trust propagation ...

The Medical Informatics Platform (MIP) of the Human Brain Project (HBP) is tasked with providing its users diverse high quality clinical data and tools for medical analysis, while complying with the national legislation about privacy and security. Data, ...

Distributed ledgers allow us to replicate databases of records across mutually untrusted parties. The best known example of distributed ledger is perhaps the Bitcoin blockchain, which maintains a consistent history of financial transactions organized as ...

Artificial Intelligent Systems are increasingly used to support early diagnosis of multiple relevant diseases. The spread of these systems is boosted by the application of machine learning techniques on datasets (also in the form of videos and images) ...

Electronic medical record (EMR) systems have now been widely adopted to support medical workers. There also has been much interest in the machine-based generation of clinical pathways that can utilize sequential pattern mining (SPM) to extract them from ...

In this work we face the challenge of estimating a ship's main-engine rotational speed from vessel data series, in the context of sea vessel route optimization. To this end, we study the value of different vessel data types as predictors of the engine ...

Although Bitcoin is a relatively new subject in Economics, contributions in this topic are growing very fast. Several papers evidenced a bubble behaviour in exchange rates between Bitcoin and traditional currencies. In this paper we explore and give ...

Many context-aware recommendation methods extract contexts from reviews using supervised methods. However, this requires the optimal values for contexts to be predefined, which is not a trivial task. Although some approaches have avoided this by ...

This paper raises the privacy issues related to information that is accessible about individuals from their mobile devices and that which is collected when they interact with and use so called "free" services provided on the web. The importance of ...

The field of artificial intelligence (AI) is constantly growing and finding new ways to solve real world problems. One of the AI knowledge and research fields is natural language processing (NLP) which attempts to categorise and process human language ...

In this paper, we build on top of the MalConv neural networks learning architecture which was initially designed for malware/benign classification. We evaluate the transfer learning of MalConv for malware multi-class classification by extending its ...

The market for invoice financing has been steadily growing in the last few years and has been the third financing market in size in 2016. Most solutions in this field are based on private platforms and even the new proposals based on blockchain are ...

The amount of sources and sheer volumes of spatiotemporal data have met an unprecedented growth during the last decade. As a consequence, a rapidly increasing number of applications are seeking to generate value by crunching those data. The development ...

The introduction of flash SSDs has accelerated the performance of DBMSes. However, the intrinsic characteristics of flash motivated many researchers to investigate new efficient data structures. The emergence of 3DXPoint, a new non-volatile memory, sets ...

In addition to sensor heterogeneity, monitoring applications must handle different temporal data models (e.g time series, event sequences). In this paper, we address the problem of discovering directly actionable high level knowledge from such data. We ...

The advantages offered by the presence of a schema are numerous. However, many XML documents in practice are not accompanied by a (valid) schema, making schema inference an attractive research problem. The fundamental task in XML schema learning is ...

Following technological advances carried out recently, there has been an explosion in the quantity of videos available and their accessibility. This is largely justified by the fall of the prices of acquisition and the increase of the capacity of the ...

This paper describes a data mining study of a set of ancient scripts in order to discover their relationships, including their possible common origin from a single root script. The data mining uses convolutional neural networks and support vector ...

Geo-distributed analytics is becoming an increasingly common-place as IoT, fog computing and big data processing platforms are nowadays integrating with each other. In this work, we deal with a problem encountered when complex Spark workflows run on top ...

The increasingly massive spreading of Open Government Data (OGD) is hailed as a driving force for economic and social growth, as well as an essential factor in promoting public awareness of the work of institutional decision-makers. However, this high ...

The data posting framework introduced in [8] adapts the well-known Data Exchange techniques to the new Big Data management and analysis challenges that can be found in real world scenarios. Although it is expressive enough, it requires the ability of ...

Predicting the number and the type of operations by civil protection services is essential, both to optimize on-call firefighters in size and competence, to pre-position material and human resources... To accomplish this task, it is required to possess ...