In recent years, there has been an exponential growth in the number of complex documents
and texts that require a deeper understanding of machine learning methods to be able to …

With the ever increasing size of the web, relevant information extraction on the Internet with
a query formed by a few keywords has become a big challenge. Query Expansion (QE) …

Improving the efficiency of methods has been a big challenge in recommender systems. It
has been also important to consider the trade-off between the accuracy and the computation …

Automated program repair (APR) has great potential to reduce bug-fixing effort and many
approaches have been proposed in recent years. APRs are often treated as a search …

Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to
methods for unraveling the extraordinary complexity of neuronal connectivity. From the …

Recent technological advancements have led to a deluge of data from distinctive domains
(eg, health care and scientific sensors, user-generated data, Internet and financial …

Recommender systems have developed in parallel with the web. They were initially based
on demographic, content-based and collaborative filtering. Currently, these systems are …

Ranking algorithms are deployed widely to order a set of items in applications such as
search engines, news feeds, and recommendation systems. Recent studies, however, have …

Business intelligence and analytics (BI&A) has emerged as an important area of study for
both practitioners and researchers, reflecting the magnitude and impact of data-related …

Presently, information retrieval can be accomplished simply and rapidly with the use of
search engines. This allows users to specify the search criteria as well as specific keywords …