相关论文: A Large-scale Industrial and Professional Occupati…
Occupational data mining and analysis is an important task in understanding today's industry and job market. Various machine learning techniques are proposed and gradually deployed to improve companies' operations for upstream tasks, such…
Understanding labor market dynamics is essential for policymakers, employers, and job seekers. However, comprehensive datasets that capture real-world career trajectories are scarce. In this paper, we introduce JobHop, a large-scale public…
The emergence of new and disruptive technologies makes the economy and labor market more unstable. To overcome this kind of uncertainty and to make the labor market more comprehensible, we must employ labor market intelligence techniques,…
Various stakeholders, such as researchers, government agencies, businesses, and research laboratories require a large volume of reliable scientific research outcomes including research articles and patent data to support their work. These…
An Initial Public Offering (IPO) filing is a document released when a private firm goes public, allowing individual (retail) investors to purchase its shares. These filings describe a firm's business, financials, and risks and are long,…
Data from online job postings are difficult to access and are not built in a standard or transparent manner. Data included in the standard taxonomy and occupational information database (O*NET) are updated infrequently and based on small…
Unlike human daily activities, existing publicly available sensor datasets for work activity recognition in industrial domains are limited by difficulties in collecting realistic data as close collaboration with industrial sites is…
With generative AI emerging as a general-purpose technology, understanding its economic effects is among society's most pressing questions. Existing studies of AI impact have largely relied on predictions of AI capabilities or focused…
While several public institutions provide its data openly, the effort required to access, integrate and query this data is too high, reducing the amount of possible dataset users. The Blended Integrated Open Data (BIOD) project has as…
Social media platforms have become a hub for political activities and discussions, democratizing participation in these endeavors. However, they have also become an incubator for manipulation campaigns, like information operations (IOs).…
The rapid advances in automation technologies, such as artificial intelligence (AI) and robotics, pose an increasing risk of automation for occupations, with a likely significant impact on the labour market. Recent social-economic studies…
This paper explores the evolution of occupations within the context of industry and technology life cycles, highlighting the critical yet underexplored intersection between occupational trends and broader economic dynamics. Introducing the…
Using artificial intelligence to manage IT operations, also known as AIOps, is a trend that has attracted a lot of interest and anticipation in recent years. The challenge in IT operations is to run steady-state operations without…
As the world's largest professional network, LinkedIn wants to create economic opportunity for everyone in the global workforce. One of its most critical missions is matching jobs with processionals. Improving job targeting accuracy and…
The advancement of machine learning for compiler optimization, particularly within the polyhedral model, is constrained by the scarcity of large-scale, public performance datasets. This data bottleneck forces researchers to undertake costly…
Categorization is an essential component for us to understand the world for ourselves and to communicate it collectively. It is therefore important to recognize that classification system are not necessarily static, especially for economic…
Despite data's crucial role in machine learning, most existing tools and research tend to focus on systems on top of existing data rather than how to interpret and manipulate data. In this paper, we propose DataLab, a unified data-oriented…
Open datasets play a crucial role in three research domains that intersect data science and education: learning analytics, educational data mining, and artificial intelligence in education. Researchers in these domains apply computational…
We introduce IndEgo, a multimodal egocentric and exocentric dataset addressing common industrial tasks, including assembly/disassembly, logistics and organisation, inspection and repair, woodworking, and others. The dataset contains 3,460…
Intellectual property protection(IPP) have received more and more attention recently due to the development of the global e-commerce platforms. brand recognition plays a significant role in IPP. Recent studies for brand recognition and…