Application of the Spatial Data Mining Methodology and Gamification for the Optimisation of Solving the Transport Issues of the "Varsovian Mordor"
Robert Olszewski , Agnieszka Turek
AbstractThe objective of the paper was to develop a specialised knowledge base using data mining methods, as the basis for and expert, decision making support system, created for the needs of development of action against negative spatial phenomena, which occur within the biggest office district of the capital of Poland. After collecting representative answers to a questionnaire from responders, who are professionally involved with this area, the authors “enriched the data” with commonly accessible spatial information and analysed the resulting dataset using artificial, regression and classification neural networks, CART decision trees and created fuzzy inference systems. Inference rules, developed with the use of the knowledge base and a limited amount of accessible information allow to specify highly probable types of social problems important for particular employees of this district. Using data mining techniques, the authors transformed collected data into information and knowledge, diagnosing main infrastructural and spatial problems in “Varsovian Mordor”. Generalisation of inference rules, developed as a result of knowledge acquisition allowed the authors to propose unique, social gamification techniques, precisely dedicated for particular groups of inhabitants and employees of “the Mordor”.
|Publication size in sheets||0.55|
|Book||Tan Ying, Shi Yuhui (eds.): Proceedings of Data Mining and Big Data. First International Conference, DMBD 2016, Lecture Notes In Computer Science, no. 9714, 2016, Springer International Publishing, ISBN 978-3-319-40972-6, [978-3-319-40973-3 (online ISBN)], DOI:10.1007/978-3-319-40973-3|
|Keywords in English||Spatial data mining, Gamification, Geoinformation society, Artificial neural networks (ANN), CART, Fuzzy inference systems (FIS), Knowledge discovery, Smart city|
|Score|| = 15.0, 29-07-2020, BookChapterSeriesAndMatConfByConferenceseries|
= 15.0, 29-07-2020, BookChapterSeriesAndMatConfByConferenceseries
|Publication indicators||= 4; = 4; = 11.0|
|Citation count*||11 (2020-09-23)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.