Digital Information Annotation System for Context-Aware Search
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Solution Overview
Problem
Current methods for annotating and sharing digital information on the web are inefficient, leading to irrelevant search results and a lack of reliable context awareness, particularly in online reviews and advertising, due to the absence of effective tools for establishing and matching digital resource contexts with user queries.
Innovation Solution
A system and method for annotating digital information using unique identifiers, allowing users to associate attributes and data with search results, and a context-aware protocol for disseminating and retrieving digital resources, which includes a client computer with a user interface and an annotation collection service that communicates with search engines and stores annotated data in a database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual processing of tags and annotations is used, then users can add custom information to digital resources, but the efficiency and accuracy of information retrieval deteriorates due to lack of context awareness
Solution Approach 1:
The patent introduces an intermediary annotation system that mediates between users and digital resources. Annotations are stored in a structured database format with standardized fields, acting as a bridge that enables efficient machine processing while preserving user-customized information. The system translates user annotations into structured data that can be quickly queried and matched with resource contexts.
Solution Approach 2:
The patent transforms unstructured user annotations into structured parameters with defined schemas. Each annotation is converted into standardized fields (e.g., title, description, tags, ratings) that can be systematically processed. This parameter transformation enables efficient filtering, sorting, and matching operations while maintaining the flexibility of user-contributed content.
2Adaptability or versatility
If conventional keyword association is used, then web pages can be grouped together, but the precision of context matching deteriorates when pages share same keywords but have different contexts
Solution Approach 1:
The patent segments the annotation structure into multiple hierarchical levels: resource-level annotations, context-level annotations, and attribute-level annotations. This segmentation allows the system to distinguish between pages that share keywords but differ in contextual attributes. Each segment can be independently queried and weighted, enabling precise context matching beyond simple keyword overlap.
Solution Approach 2:
The patent applies different quality standards and validation rules to different annotation fields based on their local requirements. Critical context fields (e.g., subject matter, intended use) have stricter validation and weighting than peripheral fields. This local quality approach ensures that context-matching decisions are driven by the most relevant attributes while maintaining flexibility in less critical areas.
3Quantity of substance
If users bookmark multiple web pages for research, then more information sources are available, but the difficulty of evaluating relevancy increases proportionally with the number of pages
Solution Approach 1:
The patent implements feedback mechanisms where the system automatically analyzes user interaction patterns with bookmarked pages and provides relevance scoring. The annotation system tracks which pages users spend time on, which they return to, and which they share, using this feedback to automatically rank and prioritize pages. This reduces the cognitive load on users by presenting pre-evaluated results rather than requiring manual assessment of each page.
Solution Approach 2:
The system performs self-service evaluation by automatically generating relevance metrics for bookmarked pages based on their annotations and usage patterns. The annotation database maintains metadata that enables automatic filtering and ranking without user intervention. This self-service capability allows the system to handle large numbers of bookmarked pages efficiently, presenting only the most relevant results to users.
Data Source
AI summary
Disclosed is an invention for methods, processes and systems that, among its enabling features and benefits, enhance retrieval of relevant information over a communication network. For instance, methods, processes and systems for performing annotation of digital information are provided. One method includes searching for items of interest using a search engine. Once the URIs associated with the item of interest are identified, a plurality of attributes are provided that may be associated with each URI. A user may provide the values for the attributes or the system may suggest values for the attributes based on information associated with each URI. Once the attributes and values are assigned, the annotated URI along with the attributes and values is stored. Another method provides for sharing of the annotated information. A user may communicate annotated information to an external storage system for sharing with other users having access to the external storage system. Another method provides for automatic updates of the annotation entries by periodically fetching the digital information associated with each URI and updating the values associated with each attribute. In addition, a system, method or process may provide a more reliable, inclusive, or otherwise effective way of collecting or identifying quality reviews for products, services, and sellers. Furthermore, a system, method or process may enable or otherwise enhance generation of actionable information for online shopping or comparative shopping. Furthermore, according to one embodiment, an interface or protocol that a computer uses to communicate with other computers is associated with a subject matter context. User-level contents or digital resources received across that interface or protocol are then associated with that subject matter context, and the computer may respond accordingly. For instance, a computer may associate a given network port with a subject matter context of shopping, and treat all digital resource requests received on that port as applying to only a shopping subject matter context. A web server may also listen on a network port associated with a subject matter context, thereby contextualizing the overall nature of the website that the web server hosts.