Clustering has primarily been used as an analytical technique to group unlabeled data for
extracting meaningful information. The fact that no clustering algorithm can solve all …

Purpose Today, big data (BD) is considered as a crucial investment for firms to stay
competitive. However, the human resource (HR) function within small-and medium-sized …

In the public safety service context, government big data governance (GBDG) is a
challenging decision-making problem that encompasses uncertainties in the arenas of big …

With rapid advances in artificial intelligence (AI), more employees are benefiting from or
being replaced by AI. Nevertheless, we know little about the extent to which AI affects …

We introduce BusinessBERT, a new industry-sensitive language model for business
applications. The key novelty of our model lies in incorporating industry information to …

Purpose To overcome the shortcomings of traditional industry classification systems such as
the Standard Industrial Classification Standard Industrial Classification, North American …

Talent is crucial for accelerating the growth of China's intelligent connected vehicle (ICV)
industry. To gain insights into talent flow within the industry, in this article, we propose the …

Extracting typical career paths from large-scale and unstructured talent profiles has recently
attracted increasing research attention. However, various challenges arise in effectively …

We propose an approach to assess, and thus, update the technology roadmapping process.
Building on extant literature, we define the ideal roadmapping process and suggest an …

Now, there are some problems in the art teaching system of colleges and universities, such
as low management efficiency. However, with the development of big data technology, big …