Towards human‐oriented solutions for deep semantic data analysis. (3rd March 2021)

• Record Type: Journal Article
• Authors: Ogiela, Lidia; Snášel, Václav
• Other Names: Ogiela Marek R. guestEditor.; Rahayu Wenny guestEditor.; Palmieri Francesco guestEditor.; Kalyanam Rajesh guestEditor.; Stankovski Vlado guestEditor.
• Is Part Of: Concurrency and computation. Volume 33:Number 19(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-03-03
• Subjects: deep data analysis -- human‐oriented solutions -- semantic description; Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.6252
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: This paper presents a new data analysis technology based on human‐oriented analysis. This analysis covers semantic methods of data description and interpretation referring to marketing preferences of system users. The proposed methods of cognitive marketing – in order to interpret fully all possible preferences which can occur – are a subject to an analysis focusing on their meaning and usefulness at the stage of product evaluation, promotion, but also regarding product distribution and price. All these processes will constitute marketing analysis due to the possibilities to assess some preferences of the analyzed data. The essence of this paper is a possibility to present the methodology of cognitive marketing based on the application of the meaning analysis which reaches the human brain and the attention attractors registered by the brain, which give rise to some interest or, quite the contrary, which remain unnoticed. A new solution is dedicated to deep semantic analysis based on the registration, processing, and analysis of attention attractors and their perception by individual person. Such attractors can be detected on the basis of observation of how attention is focused on some specific features of the examined information groups. The variety of the examined information and data can enable a wide‐ranging analysis of the issue discussed here; as a result, can assess the degree to which human attention focuses on the process of meaning interpretation of various cognitive features and observations.