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- Activity discovery (1)
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- Automation (1)
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- Embedded computing (1)
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- K-Nearest Neighbour (1)
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Articles 1 - 3 of 3
Full-Text Articles in Physical Sciences and Mathematics
Evaluating Sequence Discovery Systems In An Abstraction-Aware Manner, Eoin Rogers, Robert J. Ross, John D. Kelleher
Evaluating Sequence Discovery Systems In An Abstraction-Aware Manner, Eoin Rogers, Robert J. Ross, John D. Kelleher
Conference papers
Activity discovery is a challenging machine learning problem where we seek to uncover new or altered behavioural patterns in sensor data. In this paper we motivate and introduce a novel approach to evaluating activity discovery systems. Pre-annotated ground truths, often used to evaluate the performance of such systems on existing datasets, may exist at different levels of abstraction to the output of the output produced by the system. We propose a method for detecting and dealing with this situation, allowing for useful ground truth comparisons. This work has applications for activity discovery, and also for related fields. For example, it …
Interoperable Ocean Observing Using Archetypes: A Use-Case Based Evaluation, Paul Stacey, Damon Berry
Interoperable Ocean Observing Using Archetypes: A Use-Case Based Evaluation, Paul Stacey, Damon Berry
Conference papers
This paper presents a use-case based evaluation of the impact of two-level modeling on the automatic federation of ocean observational data. The goal of the work is to increase the interoperability and data quality of aggregated ocean observations to support convenient discovery and consumption by applications. An assessment of the interoperability of served data flows from publicly available ocean observing spatial data infrastructures was performed. Barriers to consumption of existing standards-compliant ocean-observing data streams were examined, including the impact of adherence to agreed data standards. Historical data flows were mapped to a set of archetypes and a backward integration experiment …
Validation Of Tagging Suggestion Models For A Hotel Ticketing Corpus, Bojan Bozic, Andre Rios, Sarah Jane Delany
Validation Of Tagging Suggestion Models For A Hotel Ticketing Corpus, Bojan Bozic, Andre Rios, Sarah Jane Delany
Conference papers
This paper investigates methods for the prediction of tags on a textual corpus that describes hotel staff inputs in a ticketing system. The aim is to improve the tagging process and find the most suitable method for suggesting tags for a new text entry. The paper consists of two parts: (i) exploration of existing sample data, which includes statistical analysis and visualisation of the data to provide an overview, and (ii) evaluation of tag prediction approaches. We have included different approaches from different research fields in order to cover a broad spectrum of possible solutions. As a result, we have …