Demo Data from VLDB 2026 / reviewers in the wild / expert
Fujun Zhang 0002
dblp:136/5552-2
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-1996-2571ORCID · conflict
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 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.
| Databases, data mining, and information retrieval
1 paper |
Knowledge graphs · 100% | |
| Artificial intelligence
1 paper |
Information extraction and text analysis · 50% Question answering and dialogue systems · 50% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge graphs › temporal knowledge graph
event knowledge graph |
0.7 | 1 | 2023 | What is Event Knowledge Graph: A Survey · IEEE Trans. Knowl. Data Eng. 2023 |
Natural language and speech › Information extraction and text analysis
event extraction |
0.2 | 1 | 2023 | What is Event Knowledge Graph: A Survey · IEEE Trans. Knowl. Data Eng. 2023 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | What is Event Knowledge Graph: A SurveyabstractBesides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are also an essential kind of knowledge in the world, which trigger the spring up of event-centric knowledge representation form like Event KG (EKG). It plays an increasingly important role in many downstream applications, such as search, question-answering, recommendation, financial quantitative investments, and text generation. This paper provides a comprehensive survey of EKG from history, ontology, instance, and application views. Specifically, to characterize EKG thoroughly, we focus on its history, definitions, schema induction, acquisition, related representative graphs/systems, and applications. The development processes and trends are studied therein. We further summarize prospective directions to facilitate future research on EKG. Saiping Guan, Xueqi Cheng 0001, Long Bai 0002, Fujun Zhang 0002, Zixuan Li 0001, Yutao Zeng, Xiaolong Jin 0001, Jiafeng Guo |
IEEE Trans. Knowl. Data Eng. | 4 |