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In advanced manufacturing, the incorporation of sensing technology provides an opportunity to achieve efficient in-situ process monitoring using machine learning methods. Meanwhile, the advances of information technologies also enable a…

Recent years have witnessed the resurgence of knowledge engineering which is featured by the fast growth of knowledge graphs. However, most of existing knowledge graphs are represented with pure symbols, which hurts the machine's capability…

Project management education programmes are often proposed in higher education to give students competences in project planning (Gantt's chart), project organizing, human and technical resource management, quality control and also social…

Knowledge-based machine translation (KBMT) systems have achieved excellent results in constrained domains, but have not yet scaled up to newspaper text. The reason is that knowledge resources (lexicons, grammar rules, world models) must be…

The Government of Kerala had increased the frequency of supply of free food kits owing to the pandemic, however, these items were static and not indicative of the personal preferences of the consumers. This paper conducts a comparative…

Information-maximization clustering learns a probabilistic classifier in an unsupervised manner so that mutual information between feature vectors and cluster assignments is maximized. A notable advantage of this approach is that it only…

Knowledge Management (KM) is an approach to achieving strategic objectives by visualizing, sharing, and using intangible resources of an organization and its stakeholders. There are many studies that analyze specific factors for the…

As the shortage of skilled workers continues to be a pressing issue, exacerbated by demographic change, it is becoming a critical challenge for organizations to preserve the knowledge of retiring experts and to pass it on to novices. While…

Collective decision-making is the process through which diverse stakeholders reach a joint decision. Within societal settings, one example is participatory budgeting, where constituents decide on the funding of public projects. How to most…

Cluster analysis methods seek to partition a data set into homogeneous subgroups. It is useful in a wide variety of applications, including document processing and modern genetics. Conventional clustering methods are unsupervised, meaning…

In today's uncertain and competitive market, where enterprises are subjected to increasingly shortened product life-cycles and frequent volume changes, reconfigurable manufacturing systems (RMS) applications play a significant role in the…

In recent years, the recommendation content on e-commerce platforms has become increasingly rich -- a single user feed may contain multiple entities, such as selling products, short videos, and content posts. To deal with the multi-entity…

Knowledge Management (KM) is a relatively new phenomenon that appears in the field of Public Sector Organizations (PSO) bringing new paradigms of organizational management, challenges, risks and opportunities for its implementation,…

Humans excel in analogical learning and knowledge transfer and, more importantly, possess a unique understanding of identifying appropriate sources of knowledge. From a model's perspective, this presents an interesting challenge. If models…

Being able to quickly integrate new equipment and functions into an existing plant is a major goal for both discrete and process manufacturing. But currently, these two industry domains use different approaches to achieve this goal. While…

Computations related to learning processes within an organizational social network area require some network model preparation and specific algorithms in order to implement human behaviors in simulated environments. The proposals in this…

The performance of EM in learning mixtures of product distributions often depends on the initialization. This can be problematic in crowdsourcing and other applications, e.g. when a small number of 'experts' are diluted by a large number of…

There is a growing consensus that solutions to complex science and engineering problems require novel methodologies that are able to integrate traditional physics-based modeling approaches with state-of-the-art machine learning (ML)…

In the current knowledge economy, knowledge represents the most strategically significant resource of organizations. Knowledge-intensive activities advance innovation and create and sustain economic rent and competitive advantage. In order…

This article discusses the importance of managing knowledge as a resource due to its great potential to create economic value. We detail the types of knowledge resources, the challenges associated with their management, and potential…