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Michael Gilligan

dblp:25/8315 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Smart cities and intelligent transportation › logistics
fleet management
0.112010
MineFleet®: an overview of a widely adopted distributed vehicle performance data mining system · KDD 2010
Data stream processing › stream mining
distributed stream mining
0.112010
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
YearPublicationVenuePosition
2010 MineFleet®: an overview of a widely adopted distributed vehicle performance data mining system
abstract
This 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
KDD3