Personalized Product Recommendation System Using Attribute-Based Rating
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Solution Overview
Problem
Current product review systems rely on subjective star ratings and free-form text, making it difficult for users to find relevant and applicable information, as they lack specificity and personalization, leading to ambiguity and inefficiency in product selection.
Innovation Solution
A system that allows users to rate specific product attributes using sliders and radial indicators, matching users with products based on their profiles and preferences, providing personalized recommendations and eliminating manipulation through value-neutral judgments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If star reviews with free form text are used, then product evaluation information is collected, but the information is imprecise and ambiguous
Solution Approach 1:
The patent segments the overall product evaluation into multiple specific attribute dimensions (e.g., quality, price, durability, functionality). Instead of a single star rating, users evaluate each attribute separately, transforming one ambiguous metric into multiple precise measurements that collectively provide comprehensive product assessment.
Solution Approach 2:
The patent changes the evaluation parameters from subjective star ratings to specific attribute-based metrics. By introducing dimension-specific evaluation criteria and allowing users to select attributes relevant to their needs, the system transforms vague overall impressions into quantifiable, comparable data points across different product aspects.
2Loss of information
If thousands of review paragraphs are provided, then comprehensive product feedback is available, but understanding becomes complicated and time consuming
Solution Approach 1:
The patent extracts key evaluation attributes from numerous review paragraphs and presents them as structured, condensed information. Instead of requiring users to read through thousands of text paragraphs, the system identifies and displays the most important attribute ratings and consensus opinions, filtering out redundant information while preserving essential insights.
Solution Approach 2:
The patent transforms one-dimensional text paragraphs into multi-dimensional attribute ratings that can be visually compared and filtered. By organizing feedback across multiple attribute dimensions with graphical interfaces, users can quickly grasp product evaluations without reading extensive text, reducing cognitive load and time investment.
3Productivity
If star ratings are used, then overall product judgment is provided, but the ratings are subjective and prone to manipulation
Solution Approach 1:
The patent segments the overall star rating into multiple attribute-specific ratings, making it harder to manipulate the overall impression without affecting specific dimensions. Each attribute evaluation stands independently, allowing users to identify patterns of genuine feedback versus manipulated reviews that may inflate or deflate overall ratings inconsistently across attributes.
Solution Approach 2:
The patent changes from a single subjective star rating parameter to multiple objective attribute parameters. By requiring evaluations across specific dimensions (quality, price, durability, etc.), the system creates a more reliable assessment framework where manipulation becomes more difficult and detectable, as authentic products typically maintain consistent performance across related attributes.
4Adaptability or versatility
If instructional videos are made specific to video creators, then personalized content is provided, but the videos are not applicable to audience's individual characteristics
Solution Approach 1:
The patent makes instructional videos universally applicable by tagging them with multiple attribute parameters that represent different user characteristics and needs. Instead of creating separate videos for each user type, the system allows a single video to serve multiple audiences by enabling users to filter and customize video content based on their specific attributes (skill level, device type, preferences, etc.).
Solution Approach 2:
The patent performs preliminary action by pre-tagging instructional videos with comprehensive attribute metadata during upload. This allows the system to quickly match videos with user profiles and characteristics without requiring users to manually search or specify their needs, automatically filtering and recommending appropriate content based on pre-established attribute correlations.
Data Source
AI summary
Systems and methods allow a user to input user attributes, to search for products or services, and to receive recommendations concerning items, such as products or services, based on the user attributes. A user may provide opinion information with respect to particular attributes of products or services, and may easily view and understand others' opinions regarding those particular attributes. A user may participate in a live consultation session with a person having particular knowledge with respect to a product or service. Accordingly, a user may receive highly personalized information with respect to products or services.