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In this paper, we investigate the efficiency of Co-location Pattern Mining (CPM). In popular methods for CPM, the most time-consuming step consists of identifying of pattern instances, which are required to calculate the potential interestingness ...

In the last few years, the concept of data lake has become trendy for data storage and analysis. Thus, several approaches have been proposed to build data lake systems. However, these proposals are difficult to evaluate as there are no commonly ...

Nowadays Parallel DBMSs and Spark SQL compete with each other to query Big Data. Parallel DBMSs feature extensive experience embodied by powerful data partitioning and data allocation algorithms, but they suffer when handling dynamic changes in ...

The nature of analytical queries executed either inside or outside of a DBMS increases the redundant computations due to the presence of common query sub-expressions. More recently, a few largely industry-led studies have focussed on the problem ...$$$$

This work addresses the problem of recommending lifelong pathways, i.e., sequences of actions pertaining to health, social or professional aspects, for fulfilling a personal lifelong project. This problem raises some specific challenges, since the ...

Although huge volumes of valuable data can be generated and collected at a rapid velocity from a wide variety of rich data sources, their availability may vary due to various factors. For example, in the competitive business world, huge volumes of ...

Visual Commonsense Reasoning (VCR) predicts an answer with corresponding rationale, given a question-image input. VCR is a recently introduced visual scene understanding task with a wide range of applications, including visual question answering, ...

The publication of machine-readable information has been significantly increasing both in the magnitude and complexity of the embedded relations. The Resource Description Framework (RDF) plays a big role in modelling and linking web data and their ...

In recent years, the Resource Description Framework data model has seen an increasing adoption in Web applications and IT in general. This has contributed to the establishment of standards such as the SPARQL query language and the emergence of ...

Curated Document Databases (CDD) play an important role in helping researchers find relevant articles in scientific literature. Considerable recent attention has been given to the use of various document ranking algorithms to support the ...

This study introduces an NLP framework including deep language models to automate the contextual and behavior factors extraction from a narrative text that describes the environment and pedestrian behaviors at the pedestrian encounter scenes. The ...

Text clustering has become an important task in machine learning since several micro-blogging platforms such as Twitter require efficient clustering methods to discover topics. In this context, we propose in this paper a new Spark based text ...

The present work aims to develop a text summarisation system for financial texts with a focus on the fluidity of the target language. Linguistic analysis shows that the process of writing summaries should take into account not only terminological ...

Irony detection is a text analysis problem aiming to detect ironic content. The methods in the literature are mostly for English text. In this paper, we focus on irony detection in Turkish and we analyze the explainability of neural models using ...

Graph analytics is important in data science research, where Python is nowadays the most popular language among data analysts. It facilitates many packages for graph analytics. However, those packages are either too specific or cannot work on ...

Clustering is a data analysis method for extracting knowledge by discovering groups of data called clusters. Density-based clustering methods have proven to be effective for arbitrary-shaped clusters, but they have difficulties to find low-density ...

Datasets from different domains usually contain data defined over a wide set of attributes or features linked through correlation relationship. Moreover, there are some applications in which not all the attributes should be treated in the same ...

The problem of identifying the degree of semantic similarity between two textual statements automatically has grown in importance in recent times. Its impact on various computer-related domains and recent breakthroughs in neural computation has ...

Neither a compartmentalized vision nor coupling of process data and organizational data favors the extraction of the evidence an organization needs for their business process improvement. In previous work, we dealt with integrating both kinds of ...

In this work we explore the use of a blockchain as an immutable ledger for publishing fact records in a decentralized data warehouse. We also exploit the ledger for storing smart views, i.e. definitions of frequent data cube computations in the ...

Today’s data warehousing requires continuous or on-demand data integration through a Change-Data-Capture (CDC) process to extract data deltas from Online Transaction Processing Systems. This paper proposes a workload-aware CDC framework for on-...