[PDF][PDF] Entity Type Recognition-Dealing with the Diversity of Knowledge.
F Giunchiglia, M Fumagalli - KR, 2020 - academia.edu
Semantic Heterogeneity is the problem which arises when multiple resources present
differences in how they represent the same real world phenomenon. In KR, an early …
differences in how they represent the same real world phenomenon. In KR, an early …
[HTML][HTML] Kae: A property-based method for knowledge graph alignment and extension
D Shi, X Li, F Giunchiglia - Journal of Web Semantics, 2024 - Elsevier
A common solution to the semantic heterogeneity problem is to perform knowledge graph
(KG) extension exploiting the information encoded in one or more candidate KGs, where the …
(KG) extension exploiting the information encoded in one or more candidate KGs, where the …
Towards a gateway for knowledge graph schemas collection, analysis, and embedding
M Fumagalli, M Boffo, D Shi, M Bagchi… - arXiv preprint arXiv …, 2023 - arxiv.org
One of the significant barriers to the training of statistical models on knowledge graphs is the
difficulty that scientists have in finding the best input data to address their prediction goal. In …
difficulty that scientists have in finding the best input data to address their prediction goal. In …
Recognizing entity types via properties
D Shi, F Giunchiglia - Formal Ontology in Information Systems, 2023 - ebooks.iospress.nl
The mainstream approach to the development of ontologies is merging ontologies encoding
different information, where one of the major difficulties is that the heterogeneity motivates …
different information, where one of the major difficulties is that the heterogeneity motivates …
Knowledge Graph Extension by Entity Type Recognition
D Shi - arXiv preprint arXiv:2405.02463, 2024 - arxiv.org
Knowledge graphs have emerged as a sophisticated advancement and refinement of
semantic networks, and their deployment is one of the critical methodologies in …
semantic networks, and their deployment is one of the critical methodologies in …
Liveschema: A gateway towards learning on knowledge graph schemas
M Fumagalli, M Boffo, D Shi, M Bagchi… - arXiv preprint arXiv …, 2022 - arxiv.org
One of the major barriers to the training of algorithms on knowledge graph schemas, such as
vocabularies or ontologies, is the difficulty that scientists have in finding the best input …
vocabularies or ontologies, is the difficulty that scientists have in finding the best input …
Representation heterogeneity
F Giunchiglia, M Bagchi - arXiv preprint arXiv:2207.01091, 2022 - arxiv.org
Semantic Heterogeneity is conventionally understood as the existence of variance in the
representation of a target reality when modelled, by independent parties, in different …
representation of a target reality when modelled, by independent parties, in different …
Measuring and controlling knowledge diversity
Assessing knowledge diversity may be useful for many purposes. In particular, it is
necessary to measure diversity in order to understand how it arises or is preserved; it is also …
necessary to measure diversity in order to understand how it arises or is preserved; it is also …
Ranking schemas by focus: A cognitively-inspired approach
M Fumagalli, D Shi, F Giunchiglia - … 2021, Virtual Event, September 20–22 …, 2021 - Springer
The main goal of this paper is to evaluate knowledge base schemas, modeled as a set of
entity types, each such type being associated with a set of properties, according to their …
entity types, each such type being associated with a set of properties, according to their …
Towards Ranking Schemas by Focus
M Fumagalli, D Shi, F Giunchiglia - arXiv preprint arXiv:2302.13591, 2023 - arxiv.org
The main goal of this paper is to evaluate knowledge base schemas, modeled as a set of
entity types, each such type being associated with a set of properties, according to their …
entity types, each such type being associated with a set of properties, according to their …