most citedAI-Generated Content (AIGC): A Survey

91 citations · 123 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI20231 cited

Model-as-a-Service (MaaS): A Survey

Wensheng Gan, Shicheng Wan, Philip S. Yu

Due to the increased number of parameters and data in the pre-trained model exceeding a certain level, a foundation model (e.g., a large language model) can significantly improve d…

cs.AI202391 cited

AI-Generated Content (AIGC): A Survey

Jiayang Wu, Wensheng Gan, Zefeng Chen +2

To address the challenges of digital intelligence in the digital economy, artificial intelligence-generated content (AIGC) has emerged. AIGC uses artificial intelligence to assist…

cs.CY20238 cited

Web 3.0: The Future of Internet

Wensheng Gan, Zhenqiang Ye, Shicheng Wan +1

With the rapid growth of the Internet, human daily life has become deeply bound to the Internet. To take advantage of massive amounts of data and information on the internet, the W…

cs.CY202320 cited

Web3: The Next Internet Revolution

Shicheng Wan, Hong Lin, Wensheng Gan +2

Since the first appearance of the World Wide Web, people more rely on the Web for their cyber social activities. The second phase of World Wide Web, named Web 2.0, has been extensi…

cs.AI20221 cited

Itemset Utility Maximization with Correlation Measure

Jiahui Chen, Yixin Xu, Shicheng Wan +2

As an important data mining technology, high utility itemset mining (HUIM) is used to find out interesting but hidden information (e.g., profit and risk). HUIM has been widely appl…

cs.DB20222 cited

Temporal Fuzzy Utility Maximization with Remaining Measure

Shicheng Wan, Zhenqiang Ye, Wensheng Gan +1

High utility itemset mining approaches discover hidden patterns from large amounts of temporal data. However, an inescapable problem of high utility itemset mining is that its disc…