Xichen Liu
Biographic Data
| ID | 9966646 |
|---|---|
| NAME | Xichen Liu |
| GIVEN NAMES | Xichen |
| FAMILY NAME | Liu |
| SIGNATURE | LIU X |
| AFFILIATIONS | Kunming University |
| ORCID | 0009-0001-9360-4270 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Flushed but not gone
In recent years, terms such as “brainrot,” “sludge content,” and “AI slop” have emerged almost simultaneously to describe the accelerating decay of the Internet: trashy content propelled by algorithmic dullness appears to be choking the once-vibrant online culture to death. This article argues that the convergence of these neologisms signals a deeper crisis: the problem of excess in contemporary data-intensive capitalism. Drawing on Georges Batai…
A Spatial Co-Location Pattern Mining Method Based on Hausdorff Distance Alignment
Spatial co-location patterns are used to describe the spatial associations between features, finding wide applications in geographic information systems, urban planning, and other fields. Traditional frameworks for mining spatial features typically consist of two stages: constructing spatial proximity relationships and discovering frequent patterns. However, existing methods have limitations: the construction of proximity relationships relies on …
No prominent works on this page.
A Spatial Co-Location Pattern Mining Method Based on Hausdorff Distance Alignment
Spatial co-location patterns are used to describe the spatial associations between features, finding wide applications in geographic information systems, urban planning, and other fields. Traditional frameworks for mining spatial features typically consist of two stages: constructing spatial proximity relationships and discovering frequent patterns. However, existing methods have limitations: the construction of proximity relationships relies on …
Flushed but not gone
In recent years, terms such as “brainrot,” “sludge content,” and “AI slop” have emerged almost simultaneously to describe the accelerating decay of the Internet: trashy content propelled by algorithmic dullness appears to be choking the once-vibrant online culture to death. This article argues that the convergence of these neologisms signals a deeper crisis: the problem of excess in contemporary data-intensive capitalism. Drawing on Georges Batai…
Artificial Intelligence (1 work) · Capitalism (1 work) · Choking (1 work) · Combinatorics (1 work) · Computer Science (1 work) · Content (measure theory) (1 work) · Convergence (economics) (1 work) · Data Management and Algorithms (1 work) · Data mining (1 work) · Data Mining Algorithms and Applications (1 work)