Demo Data from EDBT 2026 / reviewers in the wild / expert
Dewei Bao
dblp:204/3425
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1
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.
| Software engineering, system software, and programming languages
1 paper |
Software maintenance and evolution · 50% Empirical software engineering · 50% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
event log analysis |
0.3 | 1 | 2017 | FLAP: An End-to-End Event Log Analysis Platform for System Management · KDD 2017 |
Software maintenance and evolution
log analysis |
0.3 | 1 | 2017 | FLAP: An End-to-End Event Log Analysis Platform for System Management · KDD 2017 |
Distributed systems › fault tolerance
failure diagnosis |
0.1 | 1 | 2017 | FLAP: An End-to-End Event Log Analysis Platform for System Management · KDD 2017 |
Methods — techniques the papers use, named apart from their topics
log mining · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | FLAP: An End-to-End Event Log Analysis Platform for System ManagementabstractMany systems, such as distributed operating systems, complex networks, and high throughput web-based applications, are continuously generating large volume of event logs. These logs contain useful information to help system administrators to understand the system running status and to pinpoint the system failures. Generally, due to the scale and complexity of modern systems, the generated logs are beyond the analytic power of human beings. Therefore, it is imperative to develop a comprehensive log analysis system to support effective system management. Although a number of log mining techniques have been proposed to address specific log analysis use cases, few research and industrial efforts have been paid on providing integrated systems with an end-to-end solution to facilitate the log analysis routines. Tao Li 0001, Yexi Jiang, Chunqiu Zeng, Bin Xia 0003, Zheng Liu 0001, Wubai Zhou, Wentao Wang 0006, Dewei Bao |
KDD | 12 |