English

Cultural association based on machine learning for team formation

Human-Computer Interaction 2019-08-02 v1 Computers and Society Machine Learning

Abstract

Culture is core to human civilization, and is essential for human intellectual achievements in social context. Culture also influences how humans work together, perform particular task and overall lifestyle and dealing with other groups of civilization. Thus, culture is concerned with establishing shared ideas, particularly those playing a key role in success. Does it impact on how two individuals can work together in achieving certain goals? In this paper, we establish a means to derive cultural association and map it to culturally mediated success. Human interactions with the environment are typically in the form of expressions. Association between culture and behavior produce similar beliefs which lead to common principles and actions, while cultural similarity as a set of common expressions and responses. To measure cultural association among different candidates, we propose the use of a Graphical Association Method (GAM). The behaviors of candidates are captured through series of expressions and represented in the graphical form. The association among corresponding node and core nodes is used for the same. Our approach provides a number of interesting results and promising avenues for future applications.

Keywords

Cite

@article{arxiv.1908.00234,
  title  = {Cultural association based on machine learning for team formation},
  author = {Hrishikesh Kulkarni and Bradly Alicea},
  journal= {arXiv preprint arXiv:1908.00234},
  year   = {2019}
}

Comments

10 pages, 2 figures

R2 v1 2026-06-23T10:36:58.407Z