Demo Data from VLDB 2026 / reviewers in the wild / expert
Michael Gilligan
dblp:25/8315
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2010
—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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Smart cities and intelligent transportation · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Data stream processing · 100% | |
| Computer networks
1 paper |
Edge and fog computing · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Smart cities and intelligent transportation › logistics
fleet management |
0.1 | 1 | 2010 | MineFleet®: an overview of a widely adopted distributed vehicle performance data mining system · KDD 2010 |
Data stream processing › stream mining
distributed stream mining |
0.1 | 1 | 2010 | MineFleet®: an overview of a widely adopted distributed vehicle performance data mining system · KDD 2010 |
Methods — techniques the papers use, named apart from their topics
wireless data transmission · 0.3distributed data stream mining · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | MineFleet®: an overview of a widely adopted distributed vehicle performance data mining systemabstractThis paper describes the MineFleet distributed vehicle performance data mining system designed for commercial fleets. MineFleet analyzes high throughput data streams onboard the vehicle, generates the analytics, sends those to the remote server over the wide-area wireless networks and offers them to the fleet managers using stand-alone and web-based user-interface. The paper describes the overall architecture of the system, business needs, and shares experience from successful large-scale commercial deployments. MineFleet is probably one of the first commercially successful distributed data stream mining systems. This patented technology has been adopted, productized, and commercially offered by many large companies in the mobile resource management and GPS fleet tracking industry. This paper offers an overview of the system and offers a detailed analysis of what made it work. Hillol Kargupta, Kakali Sarkar, Michael Gilligan |
KDD | 3 |