Bookmark Aggregation via Collective Tagging and Iterative Refinement

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Solution Overview

Problem

Current systems lack an efficient method for users to store and retrieve large quantities of bookmarks, particularly failing to assist in convenient classification and retrieval through tagging, which is not effectively suggested by collective user input.

Innovation Solution

A computer-implemented system that aggregates, organizes, and retrieves bookmarks by user-specified tags, suggesting tags based on collective user input, allowing iterative refinement of search results, and enabling efficient storage and retrieval across multiple devices and online publications.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If users manually classify and organize large quantities of bookmarks, then retrieval accuracy improves, but time consumption and operational complexity increase

Engineering Contradiction:

Improveretrieval accuracyVSAvoidtime consumption

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system enables bookmarks to self-organize through automatic tag generation from user publications and collective tagging suggestions from other users, eliminating the need for manual classification while maintaining high retrieval accuracy through iterative narrowing search

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system incorporates feedback mechanisms where user tagging behavior is analyzed to generate collective tag suggestions, which are then fed back to improve the classification accuracy of future bookmark retrievals

Inventive Principle:

Principle #23Feedback

2Measurement precision

If users manually classify and organize large quantities of bookmarks, then retrieval accuracy improves, but operational ease deteriorates

Engineering Contradiction:

Improveretrieval accuracyVSAvoidoperational ease

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The system performs automatic classification by extracting tags from user publications and incorporating collective tagging suggestions, completely eliminating the need for users to manually organize bookmarks while preserving high retrieval accuracy

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system changes the parameter of classification from manual user action to automated process driven by text extraction and collective intelligence, fundamentally improving operational ease

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If bookmarks are stored across multiple devices and online publications, then system versatility improves, but system complexity increases

Engineering Contradiction:

Improvesystem versatilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system achieves universality by integrating bookmark storage across multiple devices and online publications through a unified platform that handles diverse data sources with a single set of operations, simplifying rather than complicating the user experience

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system merges bookmarks from multiple devices and publications into a unified collection, consolidating complexity on the server side while presenting a simplified interface to users

Inventive Principle:

Principle #5Merging (Combining)

Data Source

PatentUS9720965B1Bookmark aggregating, organizing and retrieving systems

Publication Date: 2017.08.01 MISKIE BENJAMIN A

AI summary

A system to assist users to bookmark online content by storing a collection of bookmarks among all the users, classifying the bookmarks by tags submitted by the users, searching the bookmarks by user specified tags returning only the bookmarks actually collected by the user, and allowing narrowing of the search by specifying additional tags. Further embodiments include limiting searching by the classification done only by the user, aggregating bookmarks across user devices and online user publications.