26 citations · 52 across the 6 of their papers we have counts for
6 papers
Provenance, Anonymisation and Data Environments: a Unifying Construction
Muhammad Aslam Jarwar, Adriane Chapman, Mark Elliot +1
The Anonymisation Decision-making Framework (ADF) operationalizes the risk management of data exchange between organizations, referred to as "data environments". The second edition…
What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot Learning for Structured Data
Yang Hu, Adriane Chapman, Guihua Wen +1
Supervised machine learning has several drawbacks that make it difficult to use in many situations. Drawbacks include: heavy reliance on massive training data, limited generalizabi…
Data provenance, curation and quality in metrology
James Cheney, Adriane Chapman, Joy Davidson +1
Data metrology -- the assessment of the quality of data -- particularly in scientific and industrial settings, has emerged as an important requirement for the UK National Physical…
Graph-based Visual-Semantic Entanglement Network for Zero-shot Image Recognition
Yang Hu, Guihua Wen, Adriane Chapman +5
Zero-shot learning uses semantic attributes to connect the search space of unseen objects. In recent years, although the deep convolutional network brings powerful visual modeling…
Dataset search: a survey
Adriane Chapman, Elena Simperl, Laura Koesten +4
Generating value from data requires the ability to find, access and make sense of datasets. There are many efforts underway to encourage data sharing and reuse, from scientific pub…
Surrogate Parenthood: Protected and Informative Graphs
Barbara Blaustein, Adriane Chapman, Len Seligman +2
Many applications, including provenance and some analyses of social networks, require path-based queries over graph-structured data. When these graphs contain sensitive information…