Joshua Akehurst

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Demo Data from VLDB 2026 / reviewers in the wild / expert

dblp:76/9924 · DBLP profile ↗

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3ranked-venue papers

1as first author

0since 2021 · last 2013

—ORCID · none

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

Human-computer interaction and ubiquitous computing · 2Artificial 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

Recommender systems · 100%

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

Topic	Weight	Papers	Last	Evidence papers
Recommender systems collaborative filtering	0.1	1	2011	CCR - A Content-Collaborative Reciprocal Recommender for Online Dating · IJCAI 2011
Recommender systems content-based recommendation	0.1	1	2011	CCR - A Content-Collaborative Reciprocal Recommender for Online Dating · IJCAI 2011
Recommender systems › user recommendation reciprocal recommendation	0.1	1	2011	CCR - A Content-Collaborative Reciprocal Recommender for Online Dating · IJCAI 2011

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

collaborative filtering · 0.1

Year	Publication	Venue	Position
2013	Recommending people to people: the nature of reciprocal recommenders with a case study in online dating Luiz Pizzato, Tomek Rej, Joshua Akehurst, Irena Koprinska, Kalina Yacef, Judy Kay	User Model. User Adapt. Interact.	3
2012	The Effect of Suspicious Profiles on People Recommenders Luiz Pizzato, Joshua Akehurst, Cameron Silvestrini, Kalina Yacef, Irena Koprinska, Judy Kay	UMAP	2
2011	CCR - A Content-Collaborative Reciprocal Recommender for Online Dating Joshua Akehurst, Irena Koprinska, Kalina Yacef, Luiz Pizzato, Judy Kay, Tomek Rej	IJCAI	1