Social Profile Search Result Sorting via Personal Similarity Scoring
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Solution Overview
Problem
Searching for individuals by their full names in social media systems often yields many similar results, making it difficult to find the specific person intended due to shared names among many users.
Innovation Solution
A system that processes search queries for social profiles by determining personal similarity scores based on shared criteria such as time frames of personal occurrences, assigning weights to these scores, and sorting results accordingly to prioritize relevant matches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If search results are retrieved based on full name matching, then the search query is simple to execute, but the number of similar results increases making it difficult to find the specific individual
Solution Approach 1:
The system changes the search parameters from simple name matching to a multi-parameter evaluation that includes personal occurrence data, time frames, and weighted similarity scores. This transforms the search mechanism to achieve more accurate results while maintaining ease of use through automated processing.
Solution Approach 2:
The system introduces an intermediary scoring mechanism that calculates personal similarity scores between the user and search results based on shared personal occurrences and time frames. This intermediary layer filters and ranks results before presentation, resolving the contradiction between simple query execution and accurate result delivery.
2Measurement precision
If multiple search criteria are considered to improve result accuracy, then search result accuracy improves, but the system complexity increases
Solution Approach 1:
The system segments the search evaluation into distinct components: personal occurrence detection, time frame analysis, similarity indication calculation, and weighted scoring. This segmentation allows complex multi-criteria evaluation to be managed through modular, independent processing stages, reducing overall system complexity while maintaining high accuracy.
3Measurement precision
If personal similarity scores are calculated based on multiple factors including time frames, then the relevance of search results improves, but the processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and storing personal occurrence data and time frame information before actual search queries are executed. This allows the search process to quickly retrieve and evaluate pre-organized data without performing complex calculations in real-time, thus improving relevance while reducing processing time.
Data Source
AI summary
The present technology includes systems and methods for searching for social profiles based on user search queries and sorting search results based on determining and matching personal similarities. In some implementations, the systems and methods retrieve a plurality of search results that either partially or fully match a search query by a user of an online community for a particular social profile. The systems and methods determine a plurality of personal similarity factors relating to the search results and compare them to the profile of the user requesting the search based on predetermined criteria and assign varying weights to the personal similarity factors. The weights are aggregated and total scores for the search results are computed. The systems and methods sort the search results based on the total scores to identify and separate results of greater interest to the user from those that of less interest.