Research on data annotation for artificial intelligence (AI) has demonstrated that biases, power, and culture impact the ways that annotators apply labels to data and subsequently affect downstream AI systems. However, annotators can only apply labels ...

Advancements in sensor technology are leading to massive collection of tracking data in sports. There is an increasing interest in analyzing the tracking data to gain competitive advantage. Analyzing and labeling key game moments can provide deep ...

HILDA brings together researchers and practitioners to exchange ideas and results on human-data interaction. It explores how data management and analysis can be made more effective when taking into account the people who design and build these processes ...

3D point cloud applications have become increasingly prevalent in diverse domains, showcasing their efficacy in various software systems. However, testing such applications presents unique challenges due to the high-dimensional nature of 3D point cloud ...

Effective prioritization of issue reports in software engineering helps to optimize resource allocation and information recovery. However, manual issue classification is laborious and lacks scalability. As an alternative, many open source software (OSS) ...

We report on the organization and results of the tool competition of the third International Workshop on Natural Language-based Software Engineering (NLBSE'24). As in prior editions, we organized the competition on automated issue report classification, ...

Many domains now leverage the benefits of Machine Learning (ML), which promises solutions that can autonomously learn to solve complex tasks by training over some data. Unfortunately, in cyberthreat detection, high-quality data is hard to come by. ...

Scientific research increasingly uses modern information-gathering methods such as crowdsourcing. There are several platforms that use the contribution of many individuals to perform specific tasks such as object identification in images. It is an ...

HILDA brings together researchers and practitioners to exchange ideas and results on human-data interaction. It explores how data management and analysis can be made more effective when taking into account the people who design and build these processes ...

Algorithmic systems have infiltrated many aspects of our society, mundane to high-stakes, and can lead to algorithmic harms known as representational and allocative. In this paper, we consider what stigma theory illuminates about mechanisms leading to ...

The problem of automatic semantic analysis in natural language processing systems is considered. It is shown that annotating semantic roles is a promising method of analysis, which consists in the recognition of predicate-argument structures in ...

Abstract---Clustering is a relevant research area in Machine Learning. The purpose of clustering is to group the objects in a dataset so that each group is made up of similar ones, which have characteristics that make them groupable, and between ...

Malicious accounts spreading misinformation has led to widespread false and misleading narratives in recent times, especially during the COVID-19 pandemic, and social media platforms struggle to eliminate these contents rapidly. This is because adapting ...

When annotators label data, a key metric for quality assurance is inter-annotator agreement (IAA): the extent to which annotators agree on their labels. Though many IAA measures exist for simple categorical and ordinal labeling tasks, relatively little ...

A well-structured and indexed database alleviates the computing burden on large data. This paper describes groundwork for presenting the data in a compact, distinctive form, improving the procedures of applying keypoint detection algorithms to preprocess ...

This research aims to build a system that estimates assessment expressions to others by machine learning, collects them in real time, and feeds them back to the participants, and this study proposes two techniques that are necessary for this purpose. ...

Point feature labeling is a classical problem in cartography and GIS that has been extensively studied for geospatial point data. At the same time, word clouds are a popular visualization tool to show the most important words in text data which has also ...

Human annotations are critical for training and evaluating supervised learning models, yet annotators often disagree with one another, especially as annotation tasks increase in complexity. A common strategy to improve label quality is to ask multiple ...

Email and other forms of electronic communication are becoming increasingly more essential to our everyday lives. However, with this growth comes the paralleled increased risk of email harassment, exacerbated by the current lack of platform support for ...

Email and other forms of electronic communication are becoming increasingly more essential to our everyday lives. However, with this growth comes the paralleled increased risk of email harassment, exacerbated by the current lack of platform support for ...