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DESERE: The 1st Workshop on Decentralised Search and Recommendation
The DESERE Workshop, our First Workshop on Decentralised Search and Recommendation, offers a platform for researchers to explore and share innovative ideas on decentralised web services, mainly focusing on three major topics: (i) societal impact of decentralised systems: their effect on privacy, policy, and regulation; (ii) decentralising applications: algorithmic and performance challenges that arise from decentralisation; and (iii) infrastructure to support decentralised systems and services: peer-to-peer networks, routing, and performance evaluation tools
Provenance, Anonymisation and Data Environments: a Unifying Construction
Based on this use case, we identify how provenance information could be utilized within the ADF framework, and identify a currently un-met requirement which is the modeling of \textit{data environments}.
What Can Knowledge Bring to Machine Learning? -- A Survey of Low-shot Learning for Structured Data
Supervised machine learning has several drawbacks that make it difficult to use in many situations.
Data provenance, curation and quality in metrology
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 Laboratory (NPL) and other national metrology institutes.
Databases
Graph-based Visual-Semantic Entanglement Network for Zero-shot Image Recognition
Zero-shot learning uses semantic attributes to connect the search space of unseen objects.
