Using a Data Mining Method to Explore Strategies for Improving the Social Interaction Environment Quality of Urban Neighborhood Open Spaces
2. The Influence of the Physical Environment on the Urban POS Social Environment
3. Methodology and Data Collection
4. Results and Discussion
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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|Greenbelt form planning (C1)||Organizational form and morphological characteristics of green space in urban public open space.||[18,20]|
|Ped and bike system (C2)||Infrastructure, paths and grounds to support walking, jogging, and biking.|||
|Waters-cape (C3)||Area, shape, and positional relationship of the water body in the place.||[6,22]|
|Arbor shrub configuration (C4)||Size, type, and collocation of trees and flowers|||
|Interior to exterior linkages (C5)||Connectivity and inter-linkages: layering and sequence from private zone to community gathering zone and neighborhood|||
|Space organization and zoning planning (C6)||Organizational distribution of subspaces or partitions|||
|Relationship with urban neighborhood (C7)||Spatial location relationship with neighboring neighborhoods|||
|Public facilities (C8)||Seating area for rest, communal spaces, special seating, talking spaces|||
|Conditional Attributes (C)||Decision Attributes (D)|
|No.||Semantic Scale||Likert Scale (5 Point)|
|C1||1. Fragmentation and scattered layout;|
2. Large area, concentrated and complete arrangement;
3. Arranged in columns, arranged according to the path.
|1: Extremely low-quality social interaction environment;|
2: Low quality social interaction environment
3: Average quality social interaction environment;
4: Higher quality social interaction environment;
5: Excellent quality social interaction environment.
|C2||1. Fully equipped (exercise bike, spinning bike, etc.);|
2. Greenway coverage for running (without supporting equipment);
3. No supporting facilities, no greenways.
|C3||1. With large lakes and rivers;|
2. Small lakes, fragmented bodies of water;
|C4||1. Complete variety, including shrubs, flowers and large trees;|
2. Fewer types of grass, small trees.
|C5||1. Multiple forms of transportation paths (public transportation vehicles, bicycles, pedestrians) and the paths radiate to connect the community;|
2. The path can only pass through (pedestrians, bicycles) and has a single path.
|C6||1. Wrap-around space;|
2. The open space;
3. Irregular spaces.
|C7||1. Centralized layout in the center of the community;|
2. Fragmented, inlaid in the neighborhoods of the community, distributed in a node-like manner.
|C8||1. Complete facilities, benches, garbage cans, drinking pool;|
2. Lack of facilities (fewer benches, no drinking pools);
3. The facilities are poor (most of them are unusable or damaged).
|Case No.||Conditional Attributes||Decision |
|Decision Attributes (D)||Core Attributes||Quality of Classification|
|Epidemic Prevention and Control Level||C1, C2, C6, C8||0.700|
|Rule No.||Conditions||Decision||Number of |
|1||(C2 = 2), (C3 = 3), (C5 = 2)||Good class (D = 1)||80%|
|2||(C7 = 2), (C8 = 1)||Good class (D = 1)||40%|
|3||(C5 = 2), (C6 = 1), (C8 = 2)||Poor class (D = 5)||28%|
|4||(C8 = 3)||Poor class (D = 5)||71%|
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Zhang, J.; Wang, G.; Xiong, L. Using a Data Mining Method to Explore Strategies for Improving the Social Interaction Environment Quality of Urban Neighborhood Open Spaces. Architecture 2023, 3, 128-136. https://doi.org/10.3390/architecture3010009
Zhang J, Wang G, Xiong L. Using a Data Mining Method to Explore Strategies for Improving the Social Interaction Environment Quality of Urban Neighborhood Open Spaces. Architecture. 2023; 3(1):128-136. https://doi.org/10.3390/architecture3010009Chicago/Turabian Style
Zhang, Jiaming, Guanqiang Wang, and Lei Xiong. 2023. "Using a Data Mining Method to Explore Strategies for Improving the Social Interaction Environment Quality of Urban Neighborhood Open Spaces" Architecture 3, no. 1: 128-136. https://doi.org/10.3390/architecture3010009