Collection Relationship Mapping via Item Overlap Analysis
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Solution Overview
Problem
In multi-user environments, users face difficulties in locating related items or collections within an item universe due to the large number of curated collections, which can lead to inefficient browsing and discovery.
Innovation Solution
The system identifies related collections by analyzing the degree of item overlap and metadata similarity, using a Jaccard index and fuzzy string matching algorithms to establish relationships between collections, and groups similar collections into master collections for easier browsing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If users manually browse through large numbers of curated collections in an item universe, then they can discover items and collections, but the time required to locate related items increases significantly
Solution Approach 1:
The system pre-computes and stores relationships between collections by analyzing item overlaps and metadata similarities before users need them. Collection relationship data is generated in advance through automated analysis of item universe data, allowing users to immediately access pre-established relationships without performing real-time computations or manual browsing.
Solution Approach 2:
The patent introduces an intermediary layer of collection relationship data that mediates between the raw item universe and user queries. This intermediary structure pre-organizes collections based on their relationships (item overlaps, metadata similarities), allowing users to navigate through curated relationships rather than raw item lists, significantly reducing search time.
2Loss of information
If the system analyzes all collections to identify relationships, then related collections can be discovered, but the computational complexity increases
Solution Approach 1:
The analysis process is segmented into distinct phases: item overlap analysis, metadata similarity analysis, and relationship synthesis. Each phase processes specific aspects of collection relationships independently, allowing for modular computation and reducing overall complexity. The system divides the item universe into manageable analysis units that can be processed separately and then integrated.
Solution Approach 2:
The system transforms complex collection relationship analysis into parameter-based comparisons by quantifying item overlaps (using Jaccard index) and metadata similarities (using fuzzy string matching). These parameter transformations convert qualitative relationship assessment into quantitative metrics that are computationally efficient to calculate and compare at scale.
3Loss of information
If users navigate through individual collections separately, then detailed collection information is accessible, but related collections are difficult to locate
Solution Approach 1:
The patent merges information from multiple individual collections into unified collection relationships by identifying and aggregating overlapping items and similar metadata across collections. This merging creates a network of related collections that presents users with consolidated views of related content, making relationships visible without requiring users to separately examine each collection.
Solution Approach 2:
The system adds a new dimension to collection navigation by organizing collections based on their relationships rather than just their individual contents. This creates a relational dimension where collections are connected through computed relationships (item overlaps, metadata similarities), allowing users to navigate through the item universe by following relationship paths rather than traditional hierarchical or alphabetical structures.
Data Source
AI summary
Disclosed are various embodiments for identifying related collections of items within an item universe. Related collections of items can be identified based upon title similarity or a degree of overlap between collections of items. Additionally, relationships between collections of items can be generated if the collections have identical or nearly identical collection titles.