Zobrazeno 1 - 10
of 637
pro vyhledávání: '"Taylor, Kerry"'
The generic text preprocessing pipeline, comprising Tokenisation, Normalisation, Stop Words Removal, and Stemming/Lemmatisation, has been implemented in many ontology matching (OM) systems. However, the lack of standardisation in text preprocessing c
Externí odkaz:
http://arxiv.org/abs/2411.03962
Autor:
Qiang, Zhangcheng, Taylor, Kerry
Due to the dynamic nature of the semantic web, ontology version control is required to capture time-varying information, most importantly for widely-used ontologies. Despite the long-standing recognition of ontology versioning (OV) as a crucial compo
Externí odkaz:
http://arxiv.org/abs/2409.20302
Hallucinations of large language models (LLMs) commonly occur in domain-specific downstream tasks, with no exception in ontology matching (OM). The prevalence of using LLMs for OM raises the need for benchmarks to better understand LLM hallucinations
Externí odkaz:
http://arxiv.org/abs/2409.14038
Ontology matching (OM) enables semantic interoperability between different ontologies and resolves their conceptual heterogeneity by aligning related entities. OM systems currently have two prevailing design paradigms: conventional knowledge-based ex
Externí odkaz:
http://arxiv.org/abs/2312.00326
Autor:
Elazar, Nathan, Taylor, Kerry
We investigate the feasibility of using mixtures of interpretable experts (MoIE) to build interpretable image classifiers on MNIST10. MoIE uses a black-box router to assign each input to one of many inherently interpretable experts, thereby providing
Externí odkaz:
http://arxiv.org/abs/2212.00471
Data mining techniques can transform massive amounts of unstructured data into quantitative data that quickly reveal insights, trends, and patterns behind the original data. In this paper, a data mining model is applied to analyse the 2019 grant appl
Externí odkaz:
http://arxiv.org/abs/2210.16843