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2020-07-07 |
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Ontologies can differ in several axes. The following are from Approaches to Legal Ontologies:
Fernández-Barrera and Sartor (2010) divide ontologies by topology. Rooted tree is a strict is-a
taxonomy, whereas operational family has a more diverse structure, with loops.
In practice, most ontologies allow both: is-a
hierarchy as a backbone, and other relations in addition.
An ontology can be domain-specific, meant to cover a domain in fine detail. Contrast with upper ontologies, which are more general and have a small number of concepts. Core ontology is used for a general ontology within a domain: an "upper ontology" for just legal domain is better described as a legal core ontology. For more details, see [[[top_ontology_domain_ontologies]]].
A lightweight (or language-oriented) ontology is not much more than a collection of concepts: little hierarchy, few axioms. Technically, a completely flat lexicon is a lightweight ontology.
In contrast, heavyweight (more formal or highly axiomatized) ontologies have more structure. Biasiotti and Tiscornia (2010) describe as follows: "Formal ontologies are composed of a relatively small set of concepts, defined by a high number of constraints which encode the relations between individuals of classes through cardinality restrictions, property range and domain, disjointness, transitive and symmetric properties."
Ontology learning from texts is bottom-up1. Find a word in a text, relate it to other words2 and put it in an ontology. The resulting ontology has usually a high level of detail (see "Granularity"), but not a lot of structure (see "Formality").
In contrast, top-down starts from conceptual models. Take a generic concept, and build a structure by specialization. The resulting ontology is more structured--it's more likely that an ontology built top-down is heavyweight and upper, but this does not have to be the case. It's completely possible to build a lightweight, domain ontology by top-down method.
Combination of the two is called middle-out: start from the middle, generalize upwards and specialize downwards. See El Ghosh et al. (2016) for more info.
See also [[[conceptual_and_lexical_ontologies]]]
Footnotes
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Biasiotti and Tiscornia (2010) argue that legal ontologies need to be built bottom-up: "Since legal domain is strictly dependent on its own textual nature, a methodology for ontology construction must privilege a bottom–up approaches, based on a solid theoretical model." ↩
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Herbelot (2011) on ontology extraction: "— a subfield of natural language processing which, put simply, specialises in producing lists. […] Well-loved ontology extraction tasks include the retrieval of Oscar nominees, chemical reactions and dead presidents. In this kind of research, the machine is asked, for instance, to produce a list of things that are ‘like lorries’ and is expected to duly return (given the current state of the art):
truck car motorcycle plane engine hamster.
Because lorries have wheels and hamsters have too." ↩