Trusted Social Recommendation System with Weighted Filtering
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Solution Overview
Problem
Consumers face a tedious and time-consuming process when searching for trusted service providers due to the overwhelming volume of online reviews and lack of assurance about their accuracy, making it difficult to find reliable recommendations for goods and services.
Innovation Solution
A recommendation system that aggregates and presents a weighted list of recommendations based on information from trusted friends' media accounts, using a user interface on a device to display categories, sub-categories, and vendor contact information, with trust and distance weighting, and an API to communicate user selections and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If consumers use online resources to find service providers, then the availability of review-providing sites and reviewers increases, but the effort needed to vet the reviews becomes extraordinarily tedious and time-consuming
Solution Approach 1:
The patent introduces a trusted intermediary system consisting of friends and family members who act as mediators between consumers and service providers. These intermediaries pre-vet and recommend providers, eliminating the need for consumers to personally evaluate numerous reviews. The system uses social connections as trusted intermediaries to filter and validate provider information.
Solution Approach 2:
The system performs preliminary vetting and recommendation actions by friends and family members before consumers need to make decisions. Friends and family pre-evaluate service providers and create recommendation lists in advance, so when consumers need a provider, the evaluation work has already been done by trusted individuals.
2Adaptability or versatility
If consumers review multiple search engine results and rankings to find a provider, then the number of possible candidates increases, but the process becomes unwieldy and very time consuming
Solution Approach 1:
The patent extracts only the most relevant and trusted recommendations from the vast pool of available candidates. Instead of presenting consumers with all possible providers across multiple platforms, the system extracts and displays only those recommended by friends and family, filtering out unnecessary options and simplifying the decision process.
Solution Approach 2:
The system applies local quality by differentiating between trusted sources (friends and family) and untrusted sources (anonymous online reviewers). Recommendations from local social connections are given higher priority and visual prominence, while generic online reviews are de-emphasized or excluded entirely.
3Quantity of substance
If consumers rely on anonymous online reviewers, then the quantity of reviews increases, but there is no assurance that the candidate information is accurate
Solution Approach 1:
The patent replaces anonymous online reviewers with known intermediaries (friends and family) who have established trust relationships with the consumer. These intermediaries provide accountable, traceable recommendations rather than anonymous reviews, significantly improving the reliability and accuracy of information.
Solution Approach 2:
The system implements feedback mechanisms where friends and family can provide ongoing input about service providers, and consumers can provide feedback on their experiences. This creates a dynamic, accountable system where recommendation accuracy can be monitored and improved over time, unlike static anonymous reviews.
Data Source
AI summary
A recommendation platform that provides a menu of automated recommendations from on-line information by friends, with various weighting factors, to evaluate businesses. The platform is a software deployable system that amalgamates the candidate businesses into different categories and cross-references friends' experiences with these businesses. The interface utilizes a circular-like menu and is both compact and easily navigable.