Extending WordNet with UFO foundational ontology
WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Leão, Felipe [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Catalytic decomposition of 4-phenoxyphenol to aromatics over palladium catalysts supported on activated carbon aerogel bearing sulfonic acid group - 2012transfer abstract, science, services and agents on the World Wide Web, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:57 ; year:2019 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.websem.2019.02.002 |
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| 520 | |a WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. | ||
| 520 | |a WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. | ||
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10.1016/j.websem.2019.02.002 doi GBV00000000000656.pica (DE-627)ELV04714789X (ELSEVIER)S1570-8268(19)30016-2 DE-627 ger DE-627 rakwb eng 660 VZ 540 VZ 610 VZ 44.90 bkl Leão, Felipe verfasserin aut Extending WordNet with UFO foundational ontology 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. Ontology learning Elsevier Unified foundational ontology Elsevier WordNet Elsevier Semantic types Elsevier Revoredo, Kate oth Baião, Fernanda oth Enthalten in Elsevier Catalytic decomposition of 4-phenoxyphenol to aromatics over palladium catalysts supported on activated carbon aerogel bearing sulfonic acid group 2012transfer abstract science, services and agents on the World Wide Web Amsterdam [u.a.] (DE-627)ELV026326361 volume:57 year:2019 pages:0 https://doi.org/10.1016/j.websem.2019.02.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 57 2019 0 |
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10.1016/j.websem.2019.02.002 doi GBV00000000000656.pica (DE-627)ELV04714789X (ELSEVIER)S1570-8268(19)30016-2 DE-627 ger DE-627 rakwb eng 660 VZ 540 VZ 610 VZ 44.90 bkl Leão, Felipe verfasserin aut Extending WordNet with UFO foundational ontology 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. Ontology learning Elsevier Unified foundational ontology Elsevier WordNet Elsevier Semantic types Elsevier Revoredo, Kate oth Baião, Fernanda oth Enthalten in Elsevier Catalytic decomposition of 4-phenoxyphenol to aromatics over palladium catalysts supported on activated carbon aerogel bearing sulfonic acid group 2012transfer abstract science, services and agents on the World Wide Web Amsterdam [u.a.] (DE-627)ELV026326361 volume:57 year:2019 pages:0 https://doi.org/10.1016/j.websem.2019.02.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 57 2019 0 |
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10.1016/j.websem.2019.02.002 doi GBV00000000000656.pica (DE-627)ELV04714789X (ELSEVIER)S1570-8268(19)30016-2 DE-627 ger DE-627 rakwb eng 660 VZ 540 VZ 610 VZ 44.90 bkl Leão, Felipe verfasserin aut Extending WordNet with UFO foundational ontology 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. Ontology learning Elsevier Unified foundational ontology Elsevier WordNet Elsevier Semantic types Elsevier Revoredo, Kate oth Baião, Fernanda oth Enthalten in Elsevier Catalytic decomposition of 4-phenoxyphenol to aromatics over palladium catalysts supported on activated carbon aerogel bearing sulfonic acid group 2012transfer abstract science, services and agents on the World Wide Web Amsterdam [u.a.] (DE-627)ELV026326361 volume:57 year:2019 pages:0 https://doi.org/10.1016/j.websem.2019.02.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 57 2019 0 |
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10.1016/j.websem.2019.02.002 doi GBV00000000000656.pica (DE-627)ELV04714789X (ELSEVIER)S1570-8268(19)30016-2 DE-627 ger DE-627 rakwb eng 660 VZ 540 VZ 610 VZ 44.90 bkl Leão, Felipe verfasserin aut Extending WordNet with UFO foundational ontology 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. Ontology learning Elsevier Unified foundational ontology Elsevier WordNet Elsevier Semantic types Elsevier Revoredo, Kate oth Baião, Fernanda oth Enthalten in Elsevier Catalytic decomposition of 4-phenoxyphenol to aromatics over palladium catalysts supported on activated carbon aerogel bearing sulfonic acid group 2012transfer abstract science, services and agents on the World Wide Web Amsterdam [u.a.] (DE-627)ELV026326361 volume:57 year:2019 pages:0 https://doi.org/10.1016/j.websem.2019.02.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 57 2019 0 |
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10.1016/j.websem.2019.02.002 doi GBV00000000000656.pica (DE-627)ELV04714789X (ELSEVIER)S1570-8268(19)30016-2 DE-627 ger DE-627 rakwb eng 660 VZ 540 VZ 610 VZ 44.90 bkl Leão, Felipe verfasserin aut Extending WordNet with UFO foundational ontology 2019transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. Ontology learning Elsevier Unified foundational ontology Elsevier WordNet Elsevier Semantic types Elsevier Revoredo, Kate oth Baião, Fernanda oth Enthalten in Elsevier Catalytic decomposition of 4-phenoxyphenol to aromatics over palladium catalysts supported on activated carbon aerogel bearing sulfonic acid group 2012transfer abstract science, services and agents on the World Wide Web Amsterdam [u.a.] (DE-627)ELV026326361 volume:57 year:2019 pages:0 https://doi.org/10.1016/j.websem.2019.02.002 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA 44.90 Neurologie VZ AR 57 2019 0 |
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Enthalten in Catalytic decomposition of 4-phenoxyphenol to aromatics over palladium catalysts supported on activated carbon aerogel bearing sulfonic acid group Amsterdam [u.a.] volume:57 year:2019 pages:0 |
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Catalytic decomposition of 4-phenoxyphenol to aromatics over palladium catalysts supported on activated carbon aerogel bearing sulfonic acid group |
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WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. |
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WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. |
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WordNet is a large lexical database used by an uncountable number of applications for computational linguistics. Many proposals have attempted to better describe it in a semantic perspective, especially addressing synonymy, taxonomy and mereology properties, which led to very good results in domain-specific applications. A philosophical shift on this semantic description could, however, improve the scope of these results across different domains. In this direction, this work extends WordNet’s semantic knowledge by addressing philosophical meta-properties. Specifically, we apply the notion of Semantic Types to propose mapping rules between the noun synsets of Wordnet and the top-level constructs of a foundational ontology. For this task we have chosen the Unified Foundational Ontology (UFO), which explicitly exposes philosophical meta-properties of concepts in its structure, leading to a well-founded semantically-enriched version of Wordnet. The proposed rules were validated through an experiment over approximately 5,200 sample mappings, obtaining an average accuracy of 93.5% Furthermore, to show its applicability, the proposal was applied to the task of automatically learning a well-founded domain ontology. |
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