Attribute Word Scoring for Navigation POI Retrieval
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Solution Overview
Problem
Users face difficulties in selecting desired data from large retrieval results due to numerous candidates in information retrieval systems, particularly in car navigation systems, where distinguishing categories and understanding keywords is challenging, leading to increased time and effort in finding specific POI names.
Innovation Solution
An information retrieval apparatus that generates and displays attribute words associated with retrieved names, calculating scores based on relevance, independency, coverage, and equality to prioritize easily understandable attribute words for narrowing down search results, thereby reducing user effort and time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the system displays all candidate POI names matching user input, then the user can see all options, but the user requires excessive time and effort to find the desired POI among numerous candidates
Solution Approach 1:
The patent extracts and displays only the most relevant attribute words from the database that match the user's input characters, rather than showing all candidate POI names. This extraction principle filters out unnecessary information and presents only the essential matching attributes, thereby reducing the user's search time while maintaining retrieval effectiveness.
Solution Approach 2:
The patent introduces attribute words as an intermediary between the user's input and the full POI name database. These attribute words serve as a mediating layer that helps users narrow down their search without directly confronting them with the complete list of numerous POI candidates, thus reducing cognitive load and search time.
2Ease of operation
If the system provides multiple categories for narrowing search results, then the user can filter candidates more effectively, but the user becomes confused when unable to distinguish between similar categories
Solution Approach 1:
The patent applies local quality by dynamically adjusting the display of attribute words based on their relevance to the user's specific input. Instead of showing all categories uniformly, the system highlights and prioritizes attribute words that are most relevant to the current search context, making the narrowing operation easier without requiring users to understand the entire category system.
Solution Approach 2:
The patent changes the parameter of attribute word display by sorting and prioritizing attribute words based on their relevance scores to the user's input. This dynamic parameter adjustment ensures that the most relevant narrowing options are presented first, reducing user confusion while maintaining effective filtering capability.
3Ease of operation
If the system displays keywords for narrowing websites, then the user can select keywords to narrow results, but the user finds it difficult to understand whether the keyword is included in the desired data
Solution Approach 1:
The patent replaces the mechanical approach of simple keyword matching with a relevance-based sorting system. Instead of merely displaying keywords that might or might not be relevant, the system calculates and applies relevance scores to determine the display order of attribute words, making it easier for users to identify the most relevant narrowing options without needing to manually verify keyword inclusion.
Data Source
AI summary
Provided is an information retrieval method including: retrieving, by a computer, a name including input characters from a database for storing the name, an attribute word associated with the name, and a degree of relevance between the name and the attribute word; outputting the retrieved name as a candidate name; and extracting an attribute word associated with the candidate name, the extracting including: calculating a degree of independency indicating a degree of difference between the extracted attribute words, a degree of coverage indicating an extent to which the combination of the extracted attribute words covers the candidate names, and a degree of equality of a number of corresponding candidate names for each attribute word; and calculating a score of the combination of the attribute words based on at least one of the independency, the coverage and the equality to output the combinations of the attribute words to an output unit.