Spatial data mining MCQs January 8, 2026November 19, 2024 by u930973931_answers 15 min Score: 0 Attempted: 0/15 Subscribe 1. What is the primary focus of spatial data mining? (A) Discovering patterns in geographic or spatial data (B) Discovering patterns in numerical and categorical data (C) Storing spatial data in databases (D) Filtering noise from data 2. Which of the following is an example of spatial data? (A) Geographic coordinates (latitude, longitude) of a location (B) Sensor readings over time (C) Customer demographics (D) Transaction amounts in a retail store 3. In spatial data mining, what does spatial clustering aim to achieve? (A) Classifying spatial data into predefined categories (B) Identifying groups of spatial objects that are close to each other (C) Identifying outliers in spatial data (D) Reducing the dimensionality of spatial data 4. Which of the following techniques is commonly used in spatial data mining? (A) K-means clustering applied to spatial coordinates (B) Linear regression for spatial relationships (C) DBSCAN (Density-Based Spatial Clustering of Applications with Noise) (D) PCA (Principal Component Analysis) for spatial data 5. What does spatial outlier detection focus on in spatial data mining? (A) Grouping similar spatial objects together (B) Identifying points that deviate significantly from the spatial distribution of other data points (C) Predicting future locations of moving objects (D) Reducing the number of spatial features 6. Which of the following best describes the concept of spatial autocorrelation? (A) The ability of spatial data to be clustered into different categories (B) The correlation between the time of day and spatial patterns (C) The relationship between spatial and non-spatial data (D) The degree to which spatial objects in the same region are correlated with each other 7. Geographical Information Systems (GIS) are commonly used in spatial data mining to: (A) Perform web scraping of spatial data (B) Encrypt spatial data for privacy protection (C) Store and analyze spatial data (D) Conduct sentiment analysis on spatial data 8. What is the role of spatial association rule mining in spatial data mining? (A) Analyzing temporal changes in spatial data (B) Clustering spatial objects based on their similarities (C) Discovering relationships between spatial objects and their attributes (D) Reducing the dimensionality of spatial data 9. Which of the following is an example of a spatial pattern that could be mined? (A) Locations of traffic accidents and their relationship to road types (B) Temporal trends in sales data (C) Customer purchase history (D) Time series of product inventory 10. In spatial data mining, spatial regression models are used for: (A) Finding trends in time-series data (B) Reducing the number of spatial features (C) Clustering spatial objects into categories (D) Predicting spatial patterns based on spatial relationships 11. Which of the following challenges is specific to spatial data mining? (A) Data privacy concerns (B) Managing large volumes of data (C) Handling spatial dependencies and relationships (D) Handling categorical data 12. What is spatial data interpolation used for? (A) Identifying spatial outliers (B) Reducing the dimensionality of spatial data (C) Predicting unknown values at unsampled locations based on known data (D) Classifying spatial objects into predefined categories 13. In spatial data mining, what does the term “spatial-temporal data” refer to? (A) Data that includes both spatial and temporal components (B) Data that only contains temporal information (C) Data stored in spatial databases (D) Data with irrelevant temporal attributes 14. In spatial data mining, what is the purpose of spatial indexing? (A) To classify spatial data into categories (B) To anonymize spatial data (C) To organize and quickly access spatial data based on location (D) To reduce the complexity of spatial patterns 15. What does a spatial query in spatial data mining typically involve? (A) Identifying outliers in non-spatial data (B) Performing time-series analysis on spatial data (C) Searching for patterns in the spatial distribution of data (D) Grouping spatial data into categories based on predefined criteria