20 citations · 70 across the 20 of their papers we have counts for
21 papers
ConvBoost: Boosting ConvNets for Sensor-based Activity Recognition
Shuai Shao, Yu Guan, Bing Zhai +2
Human activity recognition (HAR) is one of the core research themes in ubiquitous and wearable computing. With the shift to deep learning (DL) based analysis approaches, it has bec…
Simple Yet Surprisingly Effective Training Strategies for LSTMs in Sensor-Based Human Activity Recognition
Shuai Shao, Yu Guan, Xin Guan +2
Human Activity Recognition (HAR) is one of the core research areas in mobile and wearable computing. With the application of deep learning (DL) techniques such as CNN, recognizing…
Benchmark time series data sets for PyTorch -- the torchtime package
Philip Darke, Paolo Missier, Jaume Bacardit
The development of models for Electronic Health Record data is an area of active research featuring a small number of public benchmark data sets. Researchers typically write custom…
Knowledge-driven Data Ecosystems Towards Data Transparency
Sandra Geisler, Maria-Esther Vidal, Cinzia Cappiello +9
A Data Ecosystem offers a keystone-player or alliance-driven infrastructure that enables the interaction of different stakeholders and the resolution of interoperability issues amo…
Technologies for Trustworthy Machine Learning: A Survey in a Socio-Technical Context
Ehsan Toreini, Mhairi Aitken, Kovila P. L. Coopamootoo +5
Concerns about the societal impact of AI-based services and systems has encouraged governments and other organisations around the world to propose AI policy frameworks to address f…
Building Rule Hierarchies for Efficient Logical Rule Learning from Knowledge Graphs
Yulong Gu, Yu Guan, Paolo Missier
Many systems have been developed in recent years to mine logical rules from large-scale Knowledge Graphs (KGs), on the grounds that representing regularities as rules enables both…
Towards Learning Instantiated Logical Rules from Knowledge Graphs
Yulong Gu, Yu Guan, Paolo Missier
Efficiently inducing high-level interpretable regularities from knowledge graphs (KGs) is an essential yet challenging task that benefits many downstream applications. In this work…
A customisable pipeline for continuously harvesting socially-minded Twitter users
Flavio Primo, Paolo Missier, Alexander Romanovsky +2
On social media platforms and Twitter in particular, specific classes of users such as influencers have been given satisfactory operational definitions in terms of network and cont…
Mind My Value: a decentralized infrastructure for fair and trusted IoT data trading
Paolo Missier, Shaimaa Bajoudah, Angelo Capossele +2
Internet of Things (IoT) data are increasingly viewed as a new form of massively distributed and large scale digital assets, which are continuously generated by millions of connect…
Design and evaluation of a genomics variant analysis pipeline using GATK Spark tools
Nicholas Tucci, Jacek Cala, Jannetta Steyn +1
Scalable and efficient processing of genome sequence data, i.e. for variant discovery, is key to the mainstream adoption of High Throughput technology for disease prevention and fo…
Loom: Query-aware Partitioning of Online Graphs
Hugo Firth, Paolo Missier, Jack Aiston
As with general graph processing systems, partitioning data over a cluster of machines improves the scalability of graph database management systems. However, these systems will in…
Recruiting from the network: discovering Twitter users who can help combat Zika epidemics
Paolo Missier, Callum McClean, Jonathan Carlton +5
Tropical diseases like \textit{Chikungunya} and \textit{Zika} have come to prominence in recent years as the cause of serious, long-lasting, population-wide health problems. In lar…
Preserving the value of large scale data analytics over time through selective re-computation
Paolo Missier, Jacek Cala, Maisha Rathi
A pervasive problem in Data Science is that the knowledge generated by possibly expensive analytics processes is subject to decay over time, as the data used to compute it drifts,…
The lifecycle of provenance metadata and its associated challenges and opportunities
Paolo Missier
This chapter outlines some of the challenges and opportunities associated with adopting provenance principles and standards in a variety of disciplines, including data publication…
Tracking Dengue Epidemics using Twitter Content Classification and Topic Modelling
Paolo Missier, Alexander Romanovsky, Tudor Miu +5
Detecting and preventing outbreaks of mosquito-borne diseases such as Dengue and Zika in Brasil and other tropical regions has long been a priority for governments in affected area…
The data, they are a-changin'
Paolo Missier, Jacek Cala, Eldarina Wijaya
The cost of deriving actionable knowledge from large datasets has been decreasing thanks to a convergence of positive factors: low cost data generation, inexpensively scalable stor…
TAPER: query-aware, partition-enhancement for large, heterogenous, graphs
Hugo Firth, Paolo Missier
Graph partitioning has long been seen as a viable approach to address Graph DBMS scalability. A partitioning, however, may introduce extra query processing latency unless it is sen…
YesWorkflow: A User-Oriented, Language-Independent Tool for Recovering Workflow Information from Scripts
Timothy McPhillips, Tianhong Song, Tyler Kolisnik +17
Scientific workflow management systems offer features for composing complex computational pipelines from modular building blocks, for executing the resulting automated workflows, a…
Measuring the impact of cognitive distractions on driving performance using time series analysis
Matias Garcia-Constantino, Paolo Missier, Phil Blytheand Amy Weihong Guo
Using current sensing technology, a wealth of data on driving sessions is potentially available through a combination of vehicle sensors and drivers' physiology sensors (heart rate…
ProvGen: generating synthetic PROV graphs with predictable structure
Hugo Firth, Paolo Missier
This paper introduces provGen, a generator aimed at producing large synthetic provenance graphs with predictable properties and of arbitrary size. Synthetic provenance graphs serve…
ProvAbs: model, policy, and tooling for abstracting PROV graphs
Paolo Missier, Jeremy Bryans, Carl Gamble +2
Provenance metadata can be valuable in data sharing settings, where it can be used to help data consumers form judgements regarding the reliability of the data produced by third pa…