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This research introduces the Wiki3DRank, a model combining real-time extracted quantitative data from Wikidata and Wikipedia to obtain a ranking of knowledge objects through a quantitative value that measures the relevance of one object compared to others in a specific domain. The model is based on the distribution of knowledge objects in a vector space, whose components are based on three main variables: the number of statements on Wikidata about an item, the number of articles in different Wikipedia editions, and the length in number of words of these articles. These variables are associated with the level of description of the Wikidata items, the dissemination of the referred knowledge objects in Wikipedia editions in different languages, and the degree of editorial elaboration of the corresponding Wikipedia articles. To demonstrate the viability of the model, a series of use cases across various domains are analysed: books, movies, cathedrals, earthquakes, rivers, and chemical elements. From the results obtained, it is possible to conclude that Wiki3DRank is a tool that allows measure the relevance of knowledge objects in the context of a knowledge domain. The operation of an open-source tool that enables the online calculation of Wiki3DRank is presented. The results suggest that the proposed model can be applied to different contexts and domains and that it`s ease to expand it by adding elements of weighting and extending the model with new components based on other characteristics of the encyclopaedic data of the knowledge objects, while the base vector calculation system is maintained. [ABSTRACT FROM AUTHOR]

This research introduces the Wiki3DRank, a model combining real-time extracted quantitative data from Wikidata and Wikipedia to obtain a ranking of knowledge objects through a quantitative value that measures the relevance of one object compared to others in a specific domain. The model is based on the distribution of knowledge objects in a vector space, whose components are based on three main variables: the number of statements on Wikidata about an item, the number of articles in different Wikipedia editions, and the length in number of words of these articles. These variables are associated with the level of description of the Wikidata items, the dissemination of the referred knowledge objects in Wikipedia editions in different languages, and the degree of editorial elaboration of the corresponding Wikipedia articles. To demonstrate the viability of the model, a series of use cases across various domains are analysed: books, movies, cathedrals, earthquakes, rivers, and chemical elements. From the results obtained, it is possible to conclude that Wiki3DRank is a tool that allows measure the relevance of knowledge objects in the context of a knowledge domain. The operation of an open-source tool that enables the online calculation of Wiki3DRank is presented. The results suggest that the proposed model can be applied to different contexts and domains and that it`s ease to expand it by adding elements of weighting and extending the model with new components based on other characteristics of the encyclopaedic data of the knowledge objects, while the base vector calculation system is maintained. [ABSTRACT FROM AUTHOR]

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