ACM Transactions on Intelligent Systems and Technology

This survey article presents a comprehensive analysis of crime prediction methodologies, exploring the various techniques and technologies utilized in this area. The article covers the statistical methods, machine learning algorithms, and deep learning ...

The society produces textual data online in several ways, e.g., via reviews and social media posts. Therefore, numerous researchers have been working on discovering patterns in textual data that can indicate peoples’ opinions, interests, and so on. Most ...

Temporal sequences have become pervasive in various real-world applications such as finance, spatial mobility, health records, and so on. Consequently, the volume of data generated in the form of continuous-time event sequence(s) or CTES(s) has increased ...

Outlier detection is one of the hot topics in the field of machine learning and data mining. At present, there are many kinds of outlier detection algorithms. The accuracies of traditional outlier detection algorithms are often affected by unique ...

Can a language model predict for which questions another language model will answer successfully? We investigate the extent to which performance prediction is possible and dissect various factors that influence it. Our experimental setting fine-tunes ...

Since capturing underwater images without degradation is challenging, there are few real image datasets with paired ground truth for underwater image enhancement. In this article, we propose a generative adversarial network (UIGAN) for underwater imaging; ...

With the development of computer vision technology, intelligent video surveillance systems have been developed for automatic monitoring. However, the problem of personal information protection has also emerged. Existing systems attempted to solve this ...

The conventional approach for controlling the supply temperature in collective space heating networks relies on a predefined heating curve determined by outdoor temperature and heat emitter type. This prioritises thermal comfort but lacks energetic and ...

Feature noise and label noise are ubiquitous in practical scenarios, which pose great challenges for training a robust machine learning model. Most previous approaches usually deal with only a single problem of either feature noise or label noise. However,...

In recent years, session-based recommender systems (SRSs) have emerged as a significant research focus within the recommendation field. Capturing user intentions to infer user interest accordingly has proven to be effective in enhancing the accuracy of ...

Deep Reinforcement Learning (DRL) has demonstrated promising capability in solving complex control problems. However, DRL applications in safety-critical systems are hindered by the inherent lack of robust validation techniques to assure their performance ...

Feature selection aims to identify the optimal feature subset for enhancing downstream models. Effective feature selection can remove redundant features, save computational resources, accelerate the model learning process, and improve the model overall ...

Social media users are more likely to be exposed to similar views and tend to avoid contrasting views, especially when they are part of a community of social media users. In this study, we investigate the presence of user communities and leverage them as ...

Air quality is known to be strongly correlated with respiratory diseases. Indoor air quality considerably affects human health, especially in spaces such as classrooms, where students gather and interact for long periods. Most schools are located in ...