The Unicorn in the Symbolic and Semantic Expression of the Film Director Ridley Scott in the Context of Medieval Bestiaries

Abstract

This paper observes and researches the relations between symbolic unicorn representation in Ridley Scott's movies Blade Runner and Legend comparing it to the medieval bestiary descriptions and representations. The goal in this research is to determine is Scott's imagery different from the medieval one and authors tend to research and compare that relation in this analysis. In the art of film, the unicorn most often makes its appearance as an objectively presented mythic animal, and, as such, represents the specific symbols with which it is attributed. The English film director Ridley Scott uses the motif of the Unicorn in order to expand semantic value. Scott's cinema unicorns are very similar to those in medieval bestiaries and representations, yet there are nuances in meaning which propose the specifics of this unicorn motif in contemporary representation in relation to medieval bestiaries. In the film Blade Runner (1982), the explicit symbolic and metaphorical value of the unicorn can be observed, and this can also be found (in an even more intense form) in the film Legend (1985) in which the semantic component is clearly defined by medieval bestiaries and medieval representations. The director's relationship towards this mythic animal is a reflection of his artistic approach to film, which will be investigated here in the context of the author's specifics within the film industry.

[Retracted] Analysis of Teaching Effect of Korean Education Course Based on Data Acquisition Technology

“…is study uses different classifiers for the test process, and all the data are compared and analyzed. e selected training data adopt fixed parameters and formulas (7). e training steps and process of the calculation model are the same.…”

“…In foreign countries, research on educational data mining has made some progress. For example, Babié and Vekié applied the Hadoop framework to analyze student behavior by collecting data from social networks [ 7 ]. By processing the login information of students in the system, a variety of classification methods are used to analyze and predict students' behavior.…”