Information Processing Apparatus Multi-Dimensional Vector Matching
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Solution Overview
Problem
Existing information processing systems for recommending restaurants only evaluate taste-related factors, leading to mismatched preferences and unsatisfied users.
Innovation Solution
An information processing apparatus that extracts text information from shops, generates content value vectors, calculates user preference vectors, and determines similarity between the two to evaluate content that better matches user preferences, using algorithms like Sentence-BERT and combinatorial logic for accurate matching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If restaurants are evaluated only on taste-related evaluations, then the evaluation process is simple, but user satisfaction cannot be achieved because other information on taste does not match users' preferences
Solution Approach 1:
The patent transitions from one-dimensional taste evaluation to multi-dimensional evaluation by introducing value vectors with multiple dimensions (e.g., price, location, atmosphere, service quality). This allows comprehensive assessment of restaurants beyond just taste, improving preference matching accuracy while maintaining systematic evaluation through vector-based comparison.
Solution Approach 2:
The patent changes the evaluation parameters from simple taste scores to comprehensive value vectors containing multiple attributes. By representing both restaurant characteristics and user preferences as multi-parameter vectors, the system enables precise matching through parameter comparison across multiple dimensions, resolving the contradiction between evaluation simplicity and matching accuracy.
2Reliability
If multi-dimensional content evaluation is implemented, then user preference matching improves, but the processing complexity increases
Solution Approach 1:
The patent replaces complex manual evaluation processes with automated computational systems. By using algorithms to calculate value vectors, compute similarities between restaurant and user vectors, and generate recommendations, the system achieves high recommendation accuracy while reducing operational complexity through automation rather than manual multi-dimensional assessment.
3Measurement precision
If comprehensive shop information is extracted and analyzed, then recommendation quality improves, but information processing time increases
Solution Approach 1:
The patent performs preliminary extraction and structuring of shop information into standardized value vectors in advance. By pre-processing and organizing comprehensive shop data into structured multi-dimensional vectors, the system enables efficient real-time matching operations, reducing processing time during actual recommendation generation while maintaining high matching precision through comprehensive information analysis.
Data Source
AI summary
An information processing apparatus includes a controller configured to execute operations, the operations including extracting text information regarding a shop from content of the shop, generating a content value vector in a plurality of dimensions based on the text information, calculating a person parameter for a user based on information input by the user, generating a user preference value vector in the plurality of dimensions based on the person parameter, and determining a similarity between the content value vector and the user preference value vector.