The main purpose of data mining and analytics is to find novel, potentially useful patterns that can be utilized in real-world applications derive beneficial knowledge. For identifying evaluating the usefulness different kinds patterns, many techniques constraints have been proposed, such as support, confidence, sequence order, utility parameters (e.g., weight, price, profit, quantity, satisfaction, etc.). In recent years, there has an increasing demand for utility-oriented pattern (UPM, or...

With the growing popularity of shared resources, large volumes complex data different types are collected automatically. Traditional mining algorithms generally have problems and challenges including huge memory cost, low processing speed, inadequate hard disk space. As a fundamental task mining, sequential pattern (SPM) is used in wide variety real-life applications. However, it more challenging than other tasks, i.e., frequent itemset association rule also suffers from above when handling...

Traditional education has been updated with the development of information technology in human history. Within big data and cyber-physical systems, Metaverse generated strong interest various applications (e.g., entertainment, business, cultural travel) over last decade. As a novel social work idea, consists many kinds technologies, e.g., data, interaction, artificial intelligence, game design, Internet computing, Things, blockchain. It is foreseeable that usage will contribute to...

Metaverse is a living space and cyberspace that realizes the process of virtualizing digitizing real world. It integrates plethora existing technologies with goal being able to map world, even beyond has bright future expected have many applications in various scenarios. The support based on numerous related becoming mature. Hence, there no doubt security risks development may be more prominent complex. We present some Metaverse-related potential privacy issues Metaverse. current solutions...

As a fusion of various emerging digital technologies, the Metaverse aims to build virtual shared space. It is closely related extended reality, twin, blockchain, and other technologies. Its goal space based on real world, form economic system, expand human activities, which injects new vitality into social, economic, fields. In this article, we make following contributions. We first introduce basic concepts such as development process, definition, characteristics Metaverse. After that,...

To address the challenges of digital intelligence in economy, artificial intelligence-generated content (AIGC) has emerged. AIGC uses to assist or replace manual generation by generating based on user-inputted keywords requirements. The development large model algorithms significantly strengthened capabilities AIGC, which makes products a promising generative tool and adds convenience our lives. As an upstream technology, unlimited potential support different downstream applications. It is...

The exploration of multimodal language models integrates multiple data types, such as images, text, language, audio, and other heterogeneity. While the latest large excel in text-based tasks, they often struggle to understand process types. Multimodal address this limitation by combining various modalities, enabling a more comprehensive understanding diverse data. This paper begins defining concept examining historical development algorithms. Furthermore, we introduce range products,...

The concept of a smart city is geared towards enhancing convenience and the efficient management areas through innovation. As Metaverse rises in 2020s, providing possible direction for new generation Internet, it has huge number opportunities to promote cities. can empower cities various aspects. In this article, we provide detailed review based on technologies. Firstly, introduce describe future vision applications cities, which are Metaverse. addition, discuss essential technologies...

Traditional association rule mining has been widely studied. But it is unsuitable for real‐world applications where factors such as unit profits of items and purchase quantities must be considered. High‐utility itemset (HUIM) designed to find highly profitable patterns by considering both the items. However, most HUIM algorithms are applied static databases. in market basket analysis business decision‐making, databases often dynamically updated inserting new data customer transactions....

Mining useful patterns from varied types of databases is an important research topic, which has many real-life applications. Most studies have considered the frequency as sole interestingness measure to identify high-quality patterns. However, each object different in nature. The relative importance objects not equal, terms criteria, such utility, risk, or interest. Besides, another limitation frequent that they generally a low occupancy, is, often represent small sets items transactions...

Due to the rapid growth of resource sharing, distributed systems are developed, which can be used utilize computations. Data mining ( DM ) provides powerful techniques for finding meaningful and useful information from a very large amount data, has wide range real‐world applications. However, traditional algorithms assume that data is centrally collected, memory‐resident, static. It challenging manage large‐scale process them with limited resources. For example, amounts quickly produced...

High-utility sequential pattern (HUSP) mining is an emerging topic in the field of knowledge discovery databases. It consists discovering subsequences that have a high utility (importance) sequences, which can be referred to as HUSPs. HUSPs applied many real-life applications, such market basket analysis, e-commerce recommendations, click-stream and route planning. Several algorithms been proposed efficiently mine utility-based useful patterns. However, due combinatorial explosion search...

With the rapid development of artificial intelligence technology, large language models (LLMs) have become a hot research topic. Education plays an important role in human social and progress. Traditional education faces challenges such as individual student differences, insufficient allocation teaching resources, assessment effectiveness. Therefore, applications LLMs field digital/smart broad prospects. The on educational (EduLLMs) is constantly evolving, providing new methods approaches to...

With the rapid growth of Internet, human daily life has become deeply bound to Internet. To take advantage massive amounts data and information on internet, Web architecture is continuously being reinvented upgraded. From static informative characteristics 1.0 dynamic interactive features 2.0, scholars engineers have worked hard make internet world more open, inclusive, equal. Indeed, next generation evolution (i.e., 3.0) already coming shaping our lives. 3.0 a decentralized that intelligent...

The Internet of Behavior (IoB) is a research theme that aims to analyze human behavior data on the from perspective behavioral psychology, obtain insights about behavior, and better understand intention behind behavior. In this way, IoB can predict trends in future even change which provide more convenience for life. With increasing prosperity Things (IoT), behavior-related collected by connected devices such as sensors. People are through extension IoT—the IoB. Presently, has gradually been...

In the era of Web Things, Metaverse is expected to be landing site for next generation Internet, resulting in increased popularity related technologies and applications recent years gradually becoming focus Internet research. The Metaverse, as a link between real virtual worlds, can provide users with immersive experiences. As concept grows popularity, many scholars developers begin on Metaverse's ethics core. This paper argues that should centered humans. That is, humans constitute majority...

The human ability to learn, generalize, and control complex manipulation tasks through multi-modality feedback suggests a unique capability, which we refer as dexterity intelligence. Understanding assessing this intelligence is task. Amidst the swift progress extensive proliferation of large language models (LLMs), their applications in field robotics have garnered increasing attention. LLMs possess process generate natural language, facilitating efficient interaction collaboration with...

The prevalence of online content has led to the widespread adoption recommendation systems (RSs), which serve diverse purposes such as news, advertisements, and e-commerce recommendations. Despite their significance, data scarcity issues have significantly impaired effectiveness existing RS models hindered progress. To address this challenge, concept knowledge transfer, particularly from external sources like pre-trained language models, emerges a potential solution alleviate enhance...