The purpose of this study was to define a data science architecture for talent acquisition. The approach was to propose analytics that derive data. The originality of this paper consists in proposing an architecture to work within the process of obtaining semantically enriched data by using data science and Semantic Web technologies. We applied the proposed architecture and developed a case study-based prototype that uses analytics techniques for résumé data integrated with Linked Data technologies. We conducted a case study to identify skills by applying classification via regression, k-nearest neighbors (k-NN), random forest, naïve Bayes, support vector machine, and decision tree algorithms to résumé data that we previously described with terms from publicly available ontologies. We labeled data from résumés using terms from existing human resource ontologies. The main contribution is the extraction of skills from résumés and the mining of data that was previously described with the Semantic Web.

This paper analyses the potential enhancement of e-commerce websites with Semantic web technologies from the consumers' informational perceived satisfaction point of view. Information quality is a central preoccupation in the field of business information systems' discipline and it relates to the semantic interoperability field of research. The purpose of our study is to investigate the relationship between the enhancement of product text descriptions with semantic annotations and the perceived consumers' satisfaction. We conducted and analyzed a survey questionnaire addressed to e-commerce consumers who bought online products. We found that consumers are interested in finding products with synonym names or that belong to different categories, not necessarily from the same category of products. In addition, consumers are interested about additional text descriptions on different product characteristics and on information about the importance of product characteristics. The main conclusion is that the perceived satisfaction of the online consumers is influenced by an enhanced user experience that relates to specific Semantic web technologies.

No abstract

No abstract

No abstract