POI Popularity Derivation Using Feature Word Dictionary
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Solution Overview
Problem
Existing methods for deriving popularity of Points of Interest (POIs) from social networking data face challenges in accuracy due to homonymous names and multiple POIs with the same name, requiring manual intervention for verification.
Innovation Solution
A POI popularity derivation device that generates a dictionary associating POI names with feature words, extracts relevant data based on these words, and derives popularity by counting linked data, reducing manual intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If keyword matching between POI name and posted data is simply performed, then the derivation process is simple and fast, but the accuracy of popularity derivation deteriorates due to homonymous names and multiple POIs with the same name
Solution Approach 1:
The patent introduces feature words as intermediary elements that mediate between POI names and posted data. Instead of directly matching POI names with posted data (which causes ambiguity), the system uses feature words extracted from posted data to indirectly identify and count relevant POI mentions. This intermediary mechanism resolves the contradiction by maintaining derivation speed while improving accuracy through contextual verification.
Solution Approach 2:
The patent replaces the simple mechanical keyword matching system with an automated natural language processing system. The extraction unit automatically extracts feature words from posted data, and the derivation unit automatically counts and aggregates popularity metrics based on these feature words, eliminating the need for manual visual checking while maintaining high accuracy.
2Measurement precision
If manual visual checking of posted data is performed to individually determine whether POI name appearances should be counted, then the accuracy of popularity derivation is maintained, but the complexity of the derivation process increases and manual intervention is required
Solution Approach 1:
The system implements self-service by enabling automated extraction and analysis of feature words from posted data. The extraction unit automatically identifies relevant feature words, and the derivation unit automatically performs popularity calculations based on these extracted words, eliminating the need for manual visual checking and complex human intervention while maintaining high accuracy.
Solution Approach 2:
The patent changes the parameter of analysis from direct POI name matching to feature word extraction and matching. By transforming the approach from counting exact POI name occurrences to counting posted data containing relevant feature words, the system achieves high accuracy through automated processing without requiring manual intervention or complex derivation procedures.
3Measurement precision
If feature words are assigned to each POI name to generate a popularity-assigned POI dictionary, then the accuracy of POI identification is improved, but the complexity of data processing increases
Solution Approach 1:
The patent applies preliminary action by pre-generating a popularity-assigned POI dictionary that associates POI names with their feature words before the actual popularity derivation process. This preprocessing step organizes the data structure in advance, enabling efficient and accurate matching during the derivation phase without requiring complex real-time processing, thus balancing accuracy with processing simplicity.
Data Source
AI summary
A POI popularity derivation device (10) includes: a dictionary generation unit (11) that assigns a feature word used as a co-occurrence word of a POI name to each popularity-assigned POI name serving as a popularity assignment target to generate a popularity-assigned POI dictionary in which a popularity-assigned POI name and a feature word are associated with each other; an extraction unit (12) that extracts posted data serving as a search target from posted data on the basis of predetermined criteria; and a popularity derivation unit (18) that searches for the posted data on the basis of a predetermined rule regarding feature words while referring to the popularity-assigned POI dictionary, to extract posted data linked to the popularity-assigned POI name, and derives the popularity of each popularity-assigned POI name on the basis of the number of pieces of extracted posted data for each popularity-assigned POI name.