Enhancing knowledge graphs with microdata and LLMs: the case of Schema.org and Wikidata in touristic information.
Purpose: Knowledge graphs (KGs) are structured knowledge bases that represent real-world entities and are used in a variety of applications. Many of them are created and curated from a combination of automated and manual processes. Microdata embedded in Web pages for purposes of facilitating indexin...
| Publicado en: | Electronic Library Vol. 42; no. 3; pp. 443 - 455 |
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| Autores principales: | , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Emerald Publishing Limited
2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=178064606&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 178064606 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02640473 2OJ jtl: Electronic Library issn: 02640473 maglogo: N pubinfo: dt: 2024 vid: 42 iid: 3 pid: 465 pub: Emerald Publishing Limited artinfo: ui: 178064606 178064606 178064606 10.1108/EL-06-2023-0160 178064606 ppf: 443 ppct: 12 formats: tig: atl: Enhancing knowledge graphs with microdata and LLMs: the case of Schema.org and Wikidata in touristic information. aug: au: Gonzalez-Garcia, Lino González-Carreño, Gema Rivas Machota, Ana María Padilla Fernández-Vega, Juan affil: Department of Tecnología y Ciencia, Universidad Camilo Jose Cela, Madrid, Spain and Department of Computer Science, Universidad de Alcala, Alcala de Henares, Spain sug: subj: World Wide Web Travel Health Health Information Data Management Methods Natural Language Processing Artificial Intelligence Utilization Health Knowledge Human Web Search Engines Information Retrieval Information Resources Models, Theoretical Artificial Intelligence, Generative Access to Information Data Mining ab: Purpose: Knowledge graphs (KGs) are structured knowledge bases that represent real-world entities and are used in a variety of applications. Many of them are created and curated from a combination of automated and manual processes. Microdata embedded in Web pages for purposes of facilitating indexing and search engine optimization are a potential source to augment KGs under some assumptions of complementarity and quality that have not been thoroughly explored to date. In that direction, this paper aims to report results on a study that evaluates the potential of using microdata extracted from the Web to augment the large, open and manually curated Wikidata KG for the domain of touristic information. As large corpora of Web text is currently being leveraged via large language models (LLMs), these are used to compare the effectiveness of the microdata enhancement method. Design/methodology/approach: The Schema.org taxonomy was used as the source to determine the annotation types to be collected. Here, the authors focused on tourism-related pages as a case study, selecting the relevant Schema.org concepts as point of departure. The large CommonCrawl resource was used to select those annotations from a large recent sample of the World Wide Web. The extracted annotations were processed and matched with Wikidata to estimate the degree to which microdata produced for SEO might become a valuable resource to complement KGs or vice versa. The Web pages themselves can also serve as a context to produce additional metadata elements using them as context in pipelines of an existing LLMs. That way, both the annotations and the contents itself can be used as sources. Findings: The samples extracted revealed a concentration of metadata annotations in only a few of the relevant Schema.org attributes and also revealed the possible influence of authoring tools in a significant fraction of microdata produced. The analysis of the overlapping of attributes in the sample with those of Wikidata showed the potential of the technique, limited by the disbalance of the presence of attributes. The combination of those with the use of LLMs to produce additional annotations demonstrates the feasibility of the approach in the population of existing Wikidata locations. However, in both cases, the effectiveness appears to be lower in the cases of less content in the KG, which are arguably the most relevant when considering the scenario of an automated population approach. Originality/value: The research reports novel empirical findings on the way touristic annotations with a SEO orientation are being produced in the wild and provides an assessment of their potential to complement KGs, or reuse information from those graphs. It also provides insights on the potential of using LLMs for the task. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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