Liderzy
Parallel Sessions 1: KNO-1: Knowledge Engineering and Semantic Web
- Marcin Maleszka (Wrocław University of Science and Technology)
Parallel Sessions 1: NLP-1: Natural Language Processing-1
- Andrzej Siemiński (Wrocław University of Science and Technology)
Asserting a high quality of data integration results frequently involves broadening a number of merged data sources. But does more always mean more? In this paper we apply a consensus theory, originating from the collective intelligence field, and investigate which parameters describing a collective affects the quality of its consensus, which can be treated as an output of the data...
Word embeddings are a useful tool for extracting knowledge from the free-form text contained in electronic health records, but it has become commonplace to train such word embeddings on data that do not accurately reflect how language is used in a healthcare context. We use prediction of medical codes as an example application to compare the accuracy of word embeddings trained on health...
FOKI is a formally defined framework, proposed by authors, which addresses storing, processing, and integrating ontologies. Its model is based on a mathematical apparatus but lacks a concrete syntax. These features make difficult to use standardized benchmark datasets, usually expressed in OWL2, during experimental verification of FOKI’s validity. To enable a practical usage of FOKI, a set of...
This paper reports an application of blockchains for knowledge refinement. Constructing a high-quality knowledge base is crucial for building an intelligent system. One promising approach to this task is to make use of “the wisdom of the crowd,” commonly performed through crowdsourcing. To give users proper incentives, gamification could be introduced into crowdsourcing so that users are given...
