Ebook

Learning ontology relations by combining corpus-based techniques and reasoning on data from semantic web sources

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The manual construction of formal domain conceptualizations (ontologies) is labor-intensive. Ontology learning, by contrast, provides (semi-)automatic ontology generation from input data such as domain text. This thesis proposes a novel approach for learning labels of non-taxonomic ontology relations. It combines corpus-based techniques with reasoning on Semantic Web data. Corpus-based methods apply vector space similarity of verbs co-occurring with labeled and unlabeled relations to calculate relation label suggestions from a set of candidates. A meta ontology in combination with Semantic Web sources such as DBpedia and OpenCyc allows reasoning to improve the suggested labels. An extensive formal evaluation demonstrates the superior accuracy of the presented hybrid approach.

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Ketersediaan

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Informasi Detail

Judul Seri

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No. Panggil

004.678 WOH l

Penerbit

Bern, Switzerland : Peter Lang International Academic Publishers., 2018

Deskripsi Fisik

221 p.

Bahasa

English

ISBN/ISSN

9783631606513

Klasifikasi

004.678

Tipe Isi

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Tipe Media

ebook

Tipe Pembawa

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Edisi

-

Subjek

Ontologies (Information retrieval)
Semantic Web

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

Lampiran Berkas

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