Related papers: Born to be Wild: Using Communities of Practice as …
In this article we discuss community management in interdisciplinary research teams, focusing on recognising and professionalising roles referred to here as the Research Community Managers (RCM). Drawing insights and examples from research…
Knowledge is considered an essential resource for organizations. For organizations to benefit from their possessed knowledge, knowledge needs to be managed effectively. Despite knowledge sharing and management being viewed as important by…
Farming plays a significant role in the economy by supporting related industries such as food, retail, and local services. Community-based small farms, while offering unique social and cultural benefits, face persistent challenges,…
Predicting the future direction of community evolution is a problem with high theoretical and practical significance. It allows to determine which characteristics describing communities have importance from the point of view of their future…
Knowledge plays a critical role in artificial intelligence. Recently, the extensive success of pre-trained language models (PLMs) has raised significant attention about how knowledge can be acquired, maintained, updated and used by language…
We introduce a framework for quantifying semantic variation of common words in Communities of Practice and in sets of topic-related communities. We show that while some meaning shifts are shared across related communities, others are…
The human's cognitive capacity for problem solving is always limited to his/her educational background, skills, experiences, etc. Hence, it is often insufficient to bring solution to extraordinary problems especially when there is a time…
A data commons is a cloud-based data platform with a governance structure that allows a community to manage, analyze and share its data. Data commons provide a research community with the ability to manage and analyze large datasets using…
Dynamics of a social population is analyzed taking into account some physical constraints on individual behavior and decision making abilities. The model, based on Evolutionary Game Theory, predicts that a population has to pass through a…
Knowledge distillation aims to transfer useful information from a teacher network to a student network, with the primary goal of improving the student's performance for the task at hand. Over the years, there has a been a deluge of novel…
This paper argues that a possible way to escape from the limitations of current machine learning (ML) systems is to allow their development directly by domain experts without the mediation of ML experts. This could be accomplished by making…
While commonsense knowledge acquisition and reasoning has traditionally been a core research topic in the knowledge representation and reasoning community, recent years have seen a surge of interest in the natural language processing…
Random graph models with community structure have been studied extensively in the literature. For both the problems of detecting and recovering community structure, an interesting landscape of statistical and computational phase transitions…
This paper discusses the important process of knowledge and its management, and differences between tacit and explicit knowledge and understanding the culture as a key issue for the successful implementation of knowledge management, in…
Knowledge management (KM) involves collecting, organizing, storing, and disseminating information to improve decision-making, innovation, and performance. Implementing KM at scale has become essential for organizations to effectively…
Cultural algorithm is a kind of evolutionary algorithm inspired from societal evolution and is composed of a belief space, a population space and a protocol that enables exchange of knowledge between these sources. Knowledge created in the…
Can we move beyond simply networking creative individuals to establishing diverse communities of practice for innovation through discursive methods. Furthermore, can we digitise their creativity activities within an integrative…
In this paper we study the trustworthiness of the crowd for crowdsourced software development. Through the study of literature from various domains, we present the risks that impact the trustworthiness in an enterprise context. We survey…
Knowledge distillation is a popular technique for training a small student network to emulate a larger teacher model, such as an ensemble of networks. We show that while knowledge distillation can improve student generalization, it does not…
At the frontier of most areas in science, computer simulations play a central role. The traditional division of natural science into experimental and theoretical investigations is now completely outdated. Instead, theory, simulation, and…