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Chris Colin Baillie

dblp:27/9923 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 1 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

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 · 77% Data integration and cleaning · 23%
Computer networks
1 paper
Internet of things and sensor networks · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge graphs › semantic web
linked data		 0.112011
Assessing Quality in the Web of Linked Sensor Data · AAAI 2011
Internet of things and sensor networks › sensor data management
sensor data quality		 0.112011
Assessing Quality in the Web of Linked Sensor Data · AAAI 2011
Data integration and cleaning
data quality		 0.012011
Assessing Quality in the Web of Linked Sensor Data · AAAI 2011

Methods — techniques the papers use, named apart from their topics

provenance analysis · 0.2
YearPublicationVenuePosition
2017 Linking open data and the crowd for real-time passenger information
David Corsar, Peter Edwards, John D. Nelson, Chris Colin Baillie, Konstantinos Papangelis, Nagendra R. Velaga
 J. Web Semant.4
2012 Quality Reasoning in the Semantic Web
Chris Colin Baillie, Peter Edwards, Edoardo Pignotti
 ISWC (2)1
2011 Assessing Quality in the Web of Linked Sensor Data
abstract
Assessing the quality of sensor data available on the Web is essential in order to identify reliable information for decision-making. This paper discusses how provenance of sensor observations and previous quality ratings can influence quality assessment decisions.
Chris Colin Baillie, Peter Edwards, Edoardo Pignotti
 AAAI1