Knowledge Engineering and Knowledge Management: 20th by Eva Blomqvist, Paolo Ciancarini, Francesco Poggi, Fabio

By Eva Blomqvist, Paolo Ciancarini, Francesco Poggi, Fabio Vitali

This e-book constitutes the refereed court cases of the 20 th InternationalConference on wisdom Engineering and data administration, EKAW 2016,held in Bologna, Italy, in November 2016.
The fifty one complete papers provided have been rigorously reviewed and chosen from 171 submissions. The papers conceal all elements of eliciting, buying, modeling, and handling wisdom, the development of knowledge-intensive structures and companies for the Semantic net, wisdom administration, e-business, common language processing,intelligent info integration, own electronic counsel structures, and various different comparable subject matters. a unique concentration used to be on "evolving knowledge", i.e., the impression of house and time on wisdom illustration, bearing on all elements of the administration and acquisition of data illustration of evolving, contextual, and native models.

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Extra resources for Knowledge Engineering and Knowledge Management: 20th International Conference, EKAW 2016, Bologna, Italy, November 19-23, 2016, Proceedings

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Recently, other measures have been proposed to select the most appropriate set of ontologies (which represents the BK) as the effectiveness [13] and the mapping gain [8] measures. The drawback of the proposed measures resides in the fact that they select the whole ontologies (many thousands of concepts) even if we need just for a fragment from these ones. Furthermore, dealing with whole ontologies makes it necessary to limit the number of selected ontologies. In our approach, there is no limitation of the number of selected ontologies, our units are concepts.

Locations for a sample object, extracted by computing cosine similarity on skip-gram-based vectors. 519 Distributional Representations of Entities Vector representations of words (Sect. 1) are attractive since they only require a sufficiently large text corpus with no manual annotation. However, the drawback of focusing on words is that a series of linguistic phenomena may affect the vector representation. ) is represented by a single vector where all the senses are conflated. NASARI [7], a resource containing vector representations of most of DBpedia entities, solves this problem by building a vector space of concepts.

In: ISWC, Citeseer (2010) 15. : LIMES - a time-efficient approach for large-scale link discovery on the web of data. In: IJCAI, pp. 2312–2317 (2011) 16. : RiMOM-IM: a novel iterative framework for instance matching. J. Comput. Sci. Technol. 31(1), 185– 197 (2016) 17. : LogMap: logic-based and scalable ontology matching. , Blomqvist, E. ) ISWC 2011, Part I. LNCS, vol. 7031, pp. 273–288. Springer, Heidelberg (2011) 18. : Integration of semantically annotated data by the KnoFuss architecture. , Euzenat, J.

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