The classic case pattern mining is a fundamental subject in data mining and big data science. The goal of the mining is to find correctly from a given dataset the patterns and their respective intrinsic frequentness. This paper examines two important ...

Last decades, numerous works have been concentrated on climate deregulation. While several studies have analysed the issue on a worldwide scale, few works focused on little land territories. For instance, this is the case of little islands in the ...

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 ...

Database Management Systems (DBMS) need to handle large updatable datasets in on-line transaction processing (OLTP) workloads. Most modern DBMS provide snapshots of data in multi-version concurrency control (MVCC) transaction management scheme. Each ...

This paper describes the development of AIDA, the Ancient Inscription Database and Analytics system. The AIDA system currently stores three types of ancient Minoan inscriptions: Linear A, Cretan Hieroglyph and Phaistos Disk inscriptions. In addition, ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 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 ...

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, ...

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 ...

A fundamental problem in Social Network Analysis is how to move from single-layer to multi-layer, which provide a holistic view. User profiles resolution has received considerable attention since it allows to match users on different online social ...

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 ...

In Smart grid ecosystems, it is important to carefully choose the placement of the datasets across different kind of big data systems in order to achieve high performance of the workloads and conformity with the business and data ecosystem. Our approach ...

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 ...

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 ...

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 ...