Information Processing Relevance Boost via User Relationship Distance
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Solution Overview
Problem
Conventional fulltext search engines do not consider the relevance between the searcher and the document author, leading to irrelevant documents from other teams or departments being returned with high priority, despite their lower relevance to the user's interests.
Innovation Solution
Introducing a new boost factor to measure the importance of documents based on the relevance between the searcher and the document author, represented by a quantized distance in a tree structure, which improves the relevance of searched information by considering the organizational relationship between users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional fulltext search engines are used to search for information, then the search process is simple and fast, but the relevance between the searched information and the desired information is insufficient
Solution Approach 1:
The patent introduces a user relationship model as an intermediary factor between the searcher and the searched information. By determining the relationship between the first user (searcher) and the second user (document author), the system uses this intermediary relationship to adjust and refine the relevance calculation, thereby improving information relevance without fundamentally changing the search architecture
Solution Approach 2:
The patent changes the parameter used for relevance calculation by incorporating a relationship factor derived from user relationship data. Instead of relying solely on traditional fulltext search parameters (term frequency, document frequency), the system adjusts the relevance score based on the determined user relationship, thus improving precision while maintaining system simplicity
2Measurement precision
If documents from users with different relationships are returned with high priority, then the quantity of search results is large, but the relevance to the user's interests is reduced
Solution Approach 1:
The patent applies local quality by differentiating the treatment of different documents based on the relationship between the searcher and the document author. Documents from users with closer relationships receive higher priority and better relevance scores, while documents from users with distant or no relationships are downgraded. This localized differentiation ensures that search results are tailored to the specific user relationship context
Data Source
AI summary
The present disclosure provides method and apparatus of information processing. The method comprises: in response to a request of a first user for first information, searching a database to obtain second information; determining a first relevance between a second user associated with the second information and the first user; determining a second relevance between the second information and the first information based on the first relevance; and presenting the second information to the first user based at least in part on the second relevance.