Using a Data Mining Method to Explore Strategies for Improving the Social Interaction Environment Quality of Urban Neighborhood Open Spaces

With the intensification of population aging and increasing awareness public health protection in post-epidemic era, renewal old urban community neighborhood space is facing many new challenges problems. Neighborhood Public Open Space (POS) main place for people to carry out various social activities life. The quality interaction environment that a POS can provide have vital impact on people’s well-being, as well their physical mental health. Therefore, purpose this research identify clarify key environmental design attributes/features POS, explore relationship between them from perspective creating high-quality environment. Through investigation relevant cases Shenzhen Guangzhou, China, classification performance each case elements used conditional attribute, current situation decision making attribute conduct data mining analysis. Using rough set theory, study screened four important elements: greenbelt form planning (C1); ped bike system (C2); organization zoning (C6); facilities (C8). Moreover, also presents hierarchical rules describe status matching when reaches high POS. This provides local policy makers with assessment diagnostic tools urban-built projects. results help designers draw up renovation plans basis efficiently obtaining practical experience cases, then create