Trustworthy journalism through AI
- Andreas L Opdahl,
- Bjørnar Tessem,
- Duc-Tien Dang-Nguyen,
- Enrico Motta,
- Vinay Setty,
- Eivind Throndsen,
- Are Tverberg,
- Christoph Trattner
Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid spread of ...
A design of movie script generation based on natural language processing by optimized ensemble deep learning with heuristic algorithm
Movies offer users a huge range of visual information like attractive stories. The traditional approaches have demonstrated that knowing about movie stories via only visual information is complicated. The natural data of graphical ...
A framework for investigating the dynamics of user and community sentiments in a social platform
- Gianluca Bonifazi,
- Francesco Cauteruccio,
- Enrico Corradini,
- Michele Marchetti,
- Giorgio Terracina,
- Domenico Ursino,
- Luca Virgili
Social platforms are the preferred medium for many people to express their opinions on many topics. This has led many professionals from various fields (marketing, politics, research and development, etc.) to demand increasingly ...
Logical big data integration and near real-time data analytics
In the context of decision-making, there is a growing demand for near real-time data that traditional solutions, like data warehousing based on long-running ETL processes, cannot fully meet. On the other hand, existing logical data ...
A new approach to COVID-19 data mining: A deep spatial–temporal prediction model based on tree structure for traffic revitalization index
The outbreak of the COVID-19 epidemic has had a huge impact on a global scale and its impact has covered almost all human industries. The Chinese government enacted a series of policies to restrict the transportation industry in order ...
Enhancing the convolution-based knowledge graph embeddings by increasing dimension-wise interactions
Knowledge graph embedding learns distributed low-dimensional representations for the elements in knowledge graphs, so that knowledge can be conveniently integrated into various tasks and smart systems. Recently, convolutional neural ...
An empirical evaluation of scrum training’s suitability for the model-driven development of knowledge-intensive software systems
A Product Configuration System (PCS) is a software system that facilitates the sales and production processes of defined customizable products. PCS are specific software developments in the sense that they are knowledge-intensive so ...
Automated sentimental analysis using heuristic-based CNN-BiLSTM for E-commerce dataset
The sentimental analysis is processed according to structural detection, extraction, quantification, and evaluation of impacts and information present in natural language processing, biometric data, computer-language society, and text ...
Better than XML: Towards a lexicographic markup language
This article takes a critical look at how XML is used in lexicography and asks the question, why do dictionary entries often end up looking so complex when encoded in XML? The main reason for the perceived complexity of XML-encoded ...
Highlights
- Dictionaries encoded in XML are unnecessarily verbose and complex due to overuse of purely structural markup.
Towards understanding students’ sensemaking of test case design
Software testing is the most used technique for quality assurance in industry. However, in computer science education software testing is still treated as a second-class citizen and students are unable to test their ...
Explainable machine learning models to analyse maternal health
Maternal health is a significant public health concern for globe and many developing countries. A country like India (with large population), there are considerable disparities in maternal health service utilisation and maternal ...
Highlights
- A precision healthcare strategy to advise healthcare policies using explainable machine learning models.
