Non-neighboring

The adjective 'non-neighboring' describes a relationship between two or more entities that are not situated directly adjacent to each other or do not share a common boundary. This applies to physical spaces, data points, or even abstract concepts. It emphasizes the absence of a close, contiguous proximity, implying a separation or distance. The term highlights the lack of immediate connection or influence that might be expected if entities were located in the same vicinity. This concept can apply in a variety of contexts, from geographical locations to network systems. This word often implies a lack of direct interaction or shared resources due to the spatial, temporal, or conceptual separation.

Non-neighboring meaning with examples

• The historian studied non-neighboring villages, comparing their cultural practices. These villages, geographically distant, exhibited surprising similarities. The study revealed the impact of trade routes, despite their location being non-neighboring, influencing the cultural development of the two locations. He contrasted this with neighboring villages, where there was significantly different patterns of development.
• In a social network, the concept of non-neighboring users is crucial for privacy. Two users who are non-neighboring on the network will have their social circle protected. The application might limit the data shared between non-neighboring user profiles, protecting their information. This prevents unwanted information from being shared between non-neighboring users.
• Scientists explored the relationship between non-neighboring elements in a chemical compound. The arrangement of the compound's components caused these elements to share electrons. The research revealed the surprising interactions between atoms within the compound, despite their spatial arrangement. The resulting bonding displayed an interesting dynamic among non-neighboring components.
• The city planner designed a green space network, ensuring non-neighboring parks would still be easily accessed. The plan used transportation networks to promote the ease of access. The success of this project came as a surprise as the spaces were non-neighboring. This innovative model encouraged citizen engagement.
• Analyzing a dataset, the statistician identified non-neighboring data points exhibiting correlations. The surprising connections revealed the data's underlying trends. Identifying these non-neighboring correlations proved essential in understanding the nature of the data. Further investigation revealed other points, though non-neighboring, could potentially be linked.