Abstract:
Introduction: Time and distance are the most essential factors in life. The time spent on content reveals the NLP structure and distance between key content words reveals KNN algorithm representation. One of the most widely used classification algorithms in machine learning is the K-nearest neighbor (KNN). In recent years, the trend of migration has increased tremendously as compared to a decade ago. Aims; Aim to evaluate the impact of migration in recent years using KNN to understand the most essential time-distance factors promoting such adventures. Also, revealed how time (NLP) and distance (KNN) necessitated Cameroonians' zeal for Poland and city choice. Problem: Time on data content (NLP) and distance on data content (KNN) is causing millions of pieces of information to go unnoticed. Also, a lot of cacophony has been in the air about Cameroonians scrambling in the Polish embassy for Polish visas, and in Polish borders that sends a mixed signal to social media, western world about the Cameroon government. Material and method: This study uses natural language processing to capture key comments, survey distance between key content and assess how artificial intelligence automates content to the understanding of Cameroonians to identify the most attractive communal and cultural diversity cities in Poland. The study uses questionnaires with the help of some embodiment factors that explain migration trends of most Cameroonian to Poland and choice of cities. The study uses a TF-IDF and bag of words model to identify K value for K-nearest neighbor approach and a concise NLP classified key content. Results: Based on K-nearest neighbor analysis TF-IDF and bag of words model, where results were classified into most attractive, and least attractive. Warsaw city is the most attractive communal and cultural diversity city in Poland while Gdańsk is the least. A total of 17 questionnaires reveal that Warsaw is the most attractive communal and cultural diversity city in Poland with about 49% respondents and Gdansk is the least attractive with about 2% respondents. Conclusion: Warsaw is the K-nearest city closest to Cameroonians most attractive communal and cultural diversity city. Based on K-nearest neighbor analysis, the study concluded that the fabulous and exotic facilities, services, amenities, education system, job opportunities and affordable life are amongst the reasons for the migration trends and choice of cities.
