Spatial Outlier Detection in Location Entity Datasets

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Solution Overview

Problem

Location search services face inefficiencies due to erroneous location information in large datasets, leading to incorrect placement of location identifiers on maps, which is time and labor intensive to correct manually.

Innovation Solution

A computing device is configured to arrange location entities into a hierarchy of descriptors and determine spatial outliers by analyzing the presence of other location entities within a predetermined distance, using a framework and dictionaries to segment addresses and detect outliers, thereby deleting inaccurate entries from the dataset.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual methods are used to locate and delete entities with erroneous location information, then location accuracy can be improved, but the process becomes time and labor intensive

Engineering Contradiction:

Improvelocation accuracyVSAvoidcorrection time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system performs self-correction by automatically detecting spatial outliers through hierarchical spatial indexing and distance-based outlier detection algorithms, eliminating the need for manual identification and deletion of erroneous location entities

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical processes of locating and deleting erroneous entries are replaced with automated computational methods including spatial indexing, hierarchical organization of location entities, and algorithmic outlier detection based on distance thresholds

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If large datasets of location entities are maintained to provide comprehensive location search services, then service coverage is improved, but the number of erroneous location entries increases

Engineering Contradiction:

Improveservice coverageVSAvoiddata accuracy

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The large dataset is segmented into a hierarchical structure with multiple levels of spatial organization, allowing efficient processing and analysis of location entities while maintaining comprehensive service coverage across different geographic scales

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system implements feedback mechanisms where detected spatial outliers are removed from the dataset, and the hierarchical spatial index is updated accordingly, continuously improving data accuracy while preserving comprehensive location information

Inventive Principle:

Principle #23Feedback

3Productivity

If automated detection methods are implemented to identify spatial outliers, then correction efficiency is improved, but system complexity increases

Engineering Contradiction:

Improvecorrection efficiencyVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system performs preliminary organization of location entities into a hierarchical spatial index structure before outlier detection, pre-computing spatial relationships and distances to enable efficient automated detection without requiring complex real-time calculations

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

A hierarchical spatial index structure serves as an intermediary between the raw location data and the outlier detection algorithm, simplifying the detection process by providing pre-organized spatial information and reducing the computational complexity of the overall system

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS9063226B2Detecting spatial outliers in a location entity dataset

Publication Date: 2015.06.23 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

Disclosed herein are one or more embodiments that arrange a plurality of location entities into a hierarchy of location descriptors. One or more of the disclosed embodiments may determine whether one of the location entities is a spatial outlier based at least in part on presence of one or more other location entities within a predetermined distance of the one location entity. Also, the other location entities and the one location entity may share a location descriptor.