This study innovates English network teaching by applying a refined Association Rule Mining (ARM) algorithm. It integrates an “interest” parameter into ARM, dynamically adapting content to individual learners' profiles, improving engagement and outcomes. ...

With the increase of internationalization and the exponential growth of intercultural communication, the importance of interlingual translation has become increasingly prominent. Machine translation has been a booming area of research as technology has ...

Deep reinforcement learning algorithms are increasingly used to drive decision-making systems. However, there exists a known tension between the efficiency of a machine learning algorithm and its level of explainability. Generally speaking, ...

Nowadays, guaranteeing the highest product variety in the shortest delivery time represents one of the main challenges for most of industries. The dynamic contexts where they have to compete push them to quickly readapt their processes,...

• Dynamic contexts push companies to quickly readapt their processes, increasing the need of reactive data-driven decision support tools to make the data ...

In open source communities, developers submit pull requests, either to add features, fix bugs or make any modifications to software artifacts, which can be accepted or rejected after review by a core team member of the project. Considering the large-...

Social media especially Twitter has become ubiquitous among people where they express their opinions on various domains. This paper presents a Hybrid Firefly – Ontology-based Clustering (FF-OC) algorithm which attempts to extract factors impacting a ...

In this paper, a case study of market basket analysis is conducted, using the Apriori algorithm. This method constructs a set of association rules, aiming to find the groups of products that are often purchased together. The algorithm was applied to the ...

In Intensive Medicine, the large amount of data that medical professionals are subject to can be overwhelming, leading to the use of techniques and treatments that may not be the most effective in treating patients. Should there be a need to cross ...

Many enterprise organizations own a large amount of data but suffer from methods that can't deal with it. A lot of approaches were proposed to manage big data and get the most benefits out of it. This paper proposes a complete approach for modeling ...

Customer segmentation through data mining could help companies conduct customer-oriented marketing and build differentiated strategies targeted at diverse customers. However, there has not been a guideline for systematic implementation of customer ...

Extracting association rules from large datasets has been widely studied in many variants in the last two decades; they allow to extract relations between values that occur more “often” in a database. With temporal association rules the concept has been ...

• A novel automated domain-specific knowledge graph curation framework.
• First ...

To derive meaningful insights from voluminous healthcare data, it is essential to convert it into machine understandable knowledge. Currently, machine understandable domain specific healthcare knowledge curation framework does not ...

Epilepsy is a common neurological disorder that affects millions of people worldwide. Patients with epilepsy generally require long-term antiepileptic therapy and many of them receive polypharmacy. Certain medications, including older-generation ...

Segmentation is the significant key stage in image analysis towards partitioning an image into different regions which have homogeneous features such as color, shape, and texture which is very important in classifying different region shapes in an ...

Telecommunication facilities as a media of delivering information are a mandatory facility in rail-based transportation modes. Delivering information in transportation modes can be done through visual-based information, the On-Board Passenger ...

Nowadays it is quite common for universities to use computer-supported collaborative learning (CSCL) systems to favor group learning and teaching processes. CSCL systems provide communication, coordination and collaboration tools that ease group ...

The information from Higher Education Institutions (HEIs) is primarily relevant for decision maker and educators. This study tackles e-learners behaviour using machine learning, particularly association rules and classifiers. Learners are characterized ...

This article describes how the bank industry in Taiwan must function in today's tough and fiercely competitive domestic credit card market and subdued global market. Banks are increasingly emphasizing the importance of retaining customers in order to ...

In recent years, communication technology and Internet technology are developing rapidly. In this context, people pay more and more attention to the importance of data, especially the implied information with timeliness and value, and accessing to such ...

Human behavior is complex and ambiguous. This study investigates how human beings consider two significant elements of discrete items: one side is their preference ranking relationships, while the other is their preferred temporal relationships. The ...