Personalized Entity Recommendation Delivery via HTML DOM Cloning
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Solution Overview
Problem
Current personalized entity recommendation systems face challenges in delivering recommendations across various web platforms and user devices independently of destination webpage characteristics, leading to high maintenance overhead, slow delivery, and potential flicker issues.
Innovation Solution
An intelligent WYSWYG recommendation authoring system selects a baseline entity on a destination webpage, parses its HTML DOM, maps entity attributes, and generates a recommendation definition, which is then maintained on an edge server for delivery, allowing for cloning and population into the destination webpage's DOM, independent of its characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If personalized entity recommendation systems deliver recommendations across various web platforms and user devices independently of destination webpage characteristics, then adaptability is improved, but device complexity increases
Solution Approach 1:
The patent implements a universal recommendation delivery mechanism that operates across different web platforms, browsers, and devices without requiring platform-specific templates. The system uses a standardized approach to parse and inject recommendations into destination webpages, making the system adaptable to various environments while maintaining consistent functionality.
Solution Approach 2:
The patent creates a copy of the baseline entity's HTML DOM structure and populates it with recommended entity data. This copying approach allows the recommendation system to deliver personalized content across different platforms without requiring separate templates for each destination webpage, reducing device complexity while maintaining adaptability.
2Reliability
If recommendation templates are stored on a recommendation server and delivered from server to client, then reliability is improved, but loss of time increases
Solution Approach 1:
The patent pre-parses the baseline entity's HTML DOM structure and stores it on the recommendation server. When a recommendation needs to be delivered, the system retrieves this pre-parsed structure and populates it with the recommended entity's data, eliminating the need to parse the entire destination webpage at delivery time and significantly reducing delivery time while maintaining reliability.
3Adaptability or versatility
If recommendation templates are maintained when the structure and/or style of a destination webpage changes, then adaptability is improved, but productivity decreases
Solution Approach 1:
The patent implements a self-updating mechanism where the system automatically detects changes in the destination webpage structure and re-parses the baseline entity's HTML DOM accordingly. This eliminates the need for manual template maintenance when webpage structures change, maintaining adaptability while improving productivity by automating the update process.
4Reliability
If new HTML is injected into destination webpage, then reliability is improved, but loss of time increases due to recommendation load time and flicker
Solution Approach 1:
The patent copies the pre-parsed baseline entity's HTML DOM structure and populates it with recommended entity data on the client side. This approach avoids injecting large amounts of new HTML into the destination webpage, reducing load time and eliminating flicker effects while maintaining reliable recommendation delivery.
Data Source
AI summary
Systems, methods, and computer-readable media are provided for defining personalized entity recommendations during a WYSWYG authoring experience and delivering such personalized entity recommendations. At the time of authoring, a user selects a baseline entity on a webpage where the personalized entity recommendation is to be delivered. A HTML DOM of the selected baseline entity is parsed into a plurality of HTML elements. Entity attributes associated with a recommended entity are mapped to the parsed HTML DOM generating an entity recommendation definition and the entity recommendation definition is presented enabling a user (e.g., a recommendation author) to update, edit, and/or approve the same. At runtime (i.e., at the time an entity recommendation is delivered), the HTML DOM of the selected baseline entity is cloned and the entity recommendation definition is utilized to populate entity attributes associated with the recommended entity into the HTML DOM creating a personalized entity recommendation. The personalized entity recommendation then is delivered to the destination webpage independent of the destination webpage characteristics.