Demo Data from EDBT 2026 / reviewers in the wild / expert
Shuailing Hao
dblp:371/6258
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Vision and language · 50% Language models and text generation · 50% | |
| Computer graphics and multimedia
1 paper |
Multimedia analysis and retrieval · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Vision and language
image captioning |
0.8 | 1 | 2024 | Visual Language - Let the Product Say What You Want · AAAI 2024 |
Natural language and speech › Language models and text generation › text generation › data-to-text generation
product description generation |
0.8 | 1 | 2024 | Visual Language - Let the Product Say What You Want · AAAI 2024 |
Multimedia analysis and retrieval
cross-modal retrieval |
0.8 | 1 | 2024 | Visual Language - Let the Product Say What You Want · AAAI 2024 |
Multimedia analysis and retrieval › image retrieval
product retrieval |
0.8 | 1 | 2024 | Visual Language - Let the Product Say What You Want · AAAI 2024 |
Information retrieval
e-commerce search |
0.2 | 1 | 2024 | Visual Language - Let the Product Say What You Want · AAAI 2024 |
Methods — techniques the papers use, named apart from their topics
multimodal retrieval · 2.3cross-modal generation · 2.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Visual Language - Let the Product Say What You WantabstractVisual Language is a multitasking on-line system focusing on e-commerce, which involves in generating accurate product descriptions for sellers and providing convenient product retrieval service for customers. To achieve this goal, the system adopts image description technology and multi-modal retrieval technology. By utilizing cross-modal generation technique, we could help sellers on rapid uploading products and customers on rapid retrieval, which could improve the experience of both sellers and customers. Shuailing Hao, Jing Shan, Xiaoxu Song |
AAAI | 2 |