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Microblogs have become popular media platforms for reporting and propagating news. However, they also enable the proliferation of misleading information that can cause serious damage. Thus, many efforts have been taken to defeat rumors ...

The Diversity, Equity and Inclusion (DEI) initiative started as the Diversity/Inclusion initiative in 2020 [4]. The current report summarizes our activities in 2022. Our responsibility as a community is to ensure that attendees of DB conferences feel ...

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, such proposals are difficult to evaluate as there are no commonly ...

With the increased need for data confidentiality in various applications of our daily life, homomorphic encryption (HE) has emerged as a promising cryptographic topic. HE enables to perform computations directly on encrypted data (ciphertexts) ...

Data Warehouses (DWs) are core components of Business Intelligence (BI). Missing data in DWs have a great impact on data analyses. Therefore, missing data need to be completed. Unlike other existing data imputation methods mainly adapted for facts,...

Nowadays, it is difficult for companies and organisations without Business Intelligence (BI) experts to carry out data analyses. Existing automatic data warehouse design methods cannot treat with tabular data commonly defined without schema. ...

The proliferation of rumors on social media has become a major concern due to its ability to create a devastating impact. Manually assessing the veracity of social media messages is a very time-consuming task that can be much helped by machine ...

Diversity and Inclusion (D&I) are core to fostering innovative thinking. Existing theories demonstrate that to facilitate inclusion, multiple types of exclusionary dynamics, such as self-segregation, communication apprehension, and stereotyping and ...

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 ...

Missing data occur commonly in data warehouses and may generate data usefulness problems. Thus, it is essential to address missing data to carry out a better analysis. There exists data imputation methods for missing data in fact tables, but not ...

Reputed by their low-cost, easy-access, real-time and valuable information, social media also wildly spread unverified or fake news. Rumors can notably cause severe damage on individuals and the society. Therefore, rumor detection on social media ...

In 2010, the concept of data lake emerged as an alternative to data warehouses for big data management. Data lakes follow a schema-on-read approach to provide rich and flexible analyses. However, although trendy in both the industry and academia, ...

Users of social networks tend to post and share content with little restraint. Hence, rumors and fake news can quickly spread on a huge scale. This may pose a threat to the credibility of social media and can cause serious consequences in real ...

In the current context of Big Data, a multitude of new NoSQL solutions for storing, managing, and extracting information and patterns from semi-structured data have been proposed and implemented. These solutions were developed to ...

Using data warehouses to analyse multidimensional data is a significant task in company decision-making. The need for analyzing data stored in different data warehouses generates the requirement of merging them into one integrated data warehouse. The ...

With new emerging technologies, such as satellites and drones, archaeologists collect data over large areas. However, it becomes difficult to process such data in time. Archaeological data also have many different formats (images, texts, sensor data) ...

Over the past two decades, we have witnessed an exponential increase of data production in the world. So-called big data generally come from transactional systems, and even more so from the Internet of Things and social media. They are mainly ...

Extracting top-k keywords and documents using weighting schemes are popular techniques employed in text mining and machine learning for different analysis and retrieval tasks. The weights are usually computed in the data preprocessing step, as ...