Topic Node Aggregation for Information Complexity
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Solution Overview
Problem
Navigating and aggregating large amounts of interconnected information on the internet is difficult and time-consuming due to the complexity of intersecting and non-intersecting information across vast numbers of individuals, making it challenging to automatically and accurately share accumulated knowledge.
Innovation Solution
A system that organizes information into topic nodes with text descriptions and attributes, using an information processing engine to identify and merge similar topic nodes, unify identical nodes, and classify them into a single node with combined attributes, allowing for automatic aggregation and sharing of information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If information is aggregated from vast numbers of individuals across the internet, then the quantity and diversity of information increases, but the complexity of navigating and viewing the information increases
Solution Approach 1:
The patent segments the aggregated information into hierarchical topic nodes organized in tree structures, where each node represents a specific topic or sub-topic. This segmentation allows the system to manage vast amounts of information by breaking them down into manageable, organized units that can be easily navigated and viewed without overwhelming complexity.
2Adaptability or versatility
If multiple topic nodes with similar text descriptions are maintained separately, then the diversity of information representations is preserved, but the complexity of navigating and viewing information increases
Solution Approach 1:
The patent merges topic nodes that have been determined to be similar through text comparison algorithms. When multiple topic nodes are found to describe the same or highly similar topics, they are consolidated into a single representative node, reducing redundancy and simplifying the information structure while preserving the essential diversity of information representations.
3Device complexity
If topic nodes are automatically merged based on text similarity, then information complexity is reduced, but the precision of topic classification may be compromised
Solution Approach 1:
The patent implements a feedback mechanism where topic nodes are compared using text similarity algorithms, and the results of these comparisons feed into the merging decision process. The system continuously refines its classification by evaluating text descriptions, determining similarity thresholds, and adjusting merges based on the feedback from text analysis, thereby maintaining precision while reducing complexity.
Data Source
AI summary
An accumulated information data store may include topic nodes, each having a text description of limited length and (in some cases) one or more attributes. A particular topic node may be associated as a parent topic node other child topic nodes such that the topic nodes form at least one data tree. An information processing engine may access information in the accumulated information data store and determine that a plurality of topic node text descriptions are similar and classify them as similar topic nodes. At least a part of the text description associated with one of the similar topic nodes may be selected as a favorable text description for the similar topic nodes. The system may also unify the similar topic nodes as identical topic nodes when they are currently grouped together as having the same upper tree hierarchy.