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The increasing centrality of persistent identifiers (PIDs) to scholarly ecosystems and the contribution they can make to the burgeoning 'PID graph' has the potential to transform scholarship. Despite their importance as originators of PID…
The fourth industrial revolution (4IR) is likely to have a substantial impact on the economy. Companies need to build up capabilities to implement new technologies, and automation may make some occupations obsolete. However, where, when,…
Recent years have brought significant advances to Natural Language Processing (NLP), which enabled fast progress in the field of computational job market analysis. Core tasks in this application domain are skill extraction and…
Recently, AIOps (Artificial Intelligence for IT Operations) has been well studied in academia and industry to enable automated and effective software service management. Plenty of efforts have been dedicated to AIOps, including anomaly…
Agile software development is nowadays a widely adopted practise in both open-source and industrial software projects. Agile teams typically heavily rely on issue management tools to document new issues and keep track of outstanding ones,…
The goal of this paper is to develop a multilingual classifier and conditional probability estimator of occupation codes for online job advertisements in accordance with the International Standard Classification of Occupations (ISCO)…
Dataset distillation is attracting more attention in machine learning as training sets continue to grow and the cost of training state-of-the-art models becomes increasingly high. By synthesizing datasets with high information density,…
A large amount of data is produced every second from modern information systems such as mobile devices, the world wide web, Internet of Things, social media, etc. Analysis and mining of this massive data requires a lot of advanced tools and…
This Work in Progress Research paper departs from the recent, turbulent changes in global societies, forcing many citizens to re-skill themselves to (re)gain employment. Learners therefore need to be equipped with skills to be autonomous…
The recent wave of AI and automation has been argued to differ from previous General Purpose Technologies (GPTs), in that it may lead to rapid change in occupations' underlying task requirements and persistent technological unemployment. In…
Recent estimates report that companies lose 5% of their revenue to occupational fraud. Since most medium-sized and large companies employ Enterprise Resource Planning (ERP) systems to track vast amounts of information regarding their…
Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between the research areas of machine learning, big data, streaming analytics, and the management of IT operations. AIOps,…
Process mining, as a high-level field in data mining, plays a crucial role in enhancing operational efficiency and decision-making across organizations. In this survey paper, we delve into the growing significance and ongoing trends in the…
Job security can never be taken for granted, especially in times of rapid, widespread and unexpected social and economic change. These changes can force workers to transition to new jobs. This may be because new technologies emerge or…
Many aspects of people's lives are proven to be deeply connected to their jobs. In this paper, we first investigate the distinct characteristics of major occupation categories based on tweets. From multiple social media platforms, we gather…
Semantic occupancy prediction aims to infer dense geometry and semantics of surroundings for an autonomous agent to operate safely in the 3D environment. Existing occupancy prediction methods are almost entirely trained on human-annotated…
IT systems of today are becoming larger and more complex, rendering their human supervision more difficult. Artificial Intelligence for IT Operations (AIOps) has been proposed to tackle modern IT administration challenges thanks to AI and…
It is well-established that large, diverse datasets play a pivotal role in the performance of modern AI systems for text and image modalities. However, there are no datasets for tabular data of comparable size and diversity to those…
In this study, we focused on proposing an optimal clustering mechanism for the occupations defined in the well-known US-based occupational database, O*NET. Even though all occupations are defined according to well-conducted surveys in the…
Many recent technological advances (e.g. ChatGPT and search engines) are possible only because of massive amounts of user-generated data produced through user interactions with computing systems or scraped from the web (e.g. behavior logs,…