Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

Event sequence data record series of discrete events in the time order of occurrence. They
are commonly observed in a variety of applications ranging from electronic health records to …

Moving beyond the dominant bag-of-words approach to sentiment analysis we introduce an
alternative procedure based on distributed word embeddings. The strength of word …

Data-driven intelligent transportation systems utilize data resources generated within
intelligent systems to improve the performance of transportation systems and provide …

Organizations rely on data analysts to model customer engagement, streamline operations,
improve production, inform business decisions, and combat fraud. Though numerous …

Data wrangling is a difficult and time-consuming activity in computational notebooks, and
existing wrangling tools do not fit the exploratory workflow for data scientists in these …

Many have envisioned the use of AI methods to find hidden patterns of public interest in
large volumes of data, greatly reducing the cost of investigative journalism. But so far only a …

Electronic Health Records (EHRs) have emerged as a cost-effective data source for
conducting medical research. The difficulty in using EHRs for research purposes, however …

The Internet of Things (IoT) has become widespread around the world. Since a large
number of diverse devices, such as vehicles, household electrical appliances, smart …

New trends in innovation management may require new research methods. Social media
analytics (SMA)—a method for capturing and analyzing data from user-generated content …