Contextual Content Distribution via Topic Segmentation
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Solution Overview
Problem
Existing content distribution systems fail to effectively identify and utilize sub-portions of resources related to different topics, leading to inefficient selection and presentation of content items, which can result in reduced user satisfaction and relevance of content.
Innovation Solution
The system identifies groups of terms related to different topics within a resource, determines the relevance of these terms to various portions of the resource, and selects content items based on their proximity to these topics, using a combination of term grouping, relevance scoring, and resource delineation to optimize content presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If content items are selected based on overall resource topic only, then content distribution is simplified, but content relevance to specific sub-portions decreases
Solution Approach 1:
The patent segments the resource into multiple sub-portions based on resource delineators (headings, page breaks, etc.) and identifies different topics for each sub-portion. This allows content items to be selectively presented in specific sub-portions rather than treating the entire resource as a single topic, thereby improving content relevance without requiring complete redesign of the distribution system
Solution Approach 2:
The patent applies local quality by assigning different topic characteristics to different sub-portions of the resource. Each sub-portion can have its own topic identification and content item selection, allowing content relevance to be optimized locally for each section while maintaining overall system simplicity
2Measurement precision
If multiple groups of terms related to different topics are identified, then content relevance to sub-portions improves, but system complexity increases
Solution Approach 1:
The patent performs preliminary action by identifying and grouping terms related to different topics in advance, before content item selection. This preprocessing step creates a structured understanding of the resource's topical composition, enabling more accurate content matching without adding complexity during the actual content selection process
Solution Approach 2:
The patent introduces an intermediary mechanism (term grouping and topic identification system) that bridges the resource content and content items. This intermediary layer analyzes resource content to identify sub-portions and their topics, then uses this information to guide content item selection, thereby improving relevance while managing complexity through a dedicated analysis layer
3Reliability
If content items are selected based on proximity to specific topics in sub-portions, then user satisfaction improves, but processing time increases
Solution Approach 1:
The patent segments the resource into sub-portions with distinct topics, allowing content items to be selected based on proximity to specific topic areas. This segmentation enables focused content matching in each sub-portion rather than analyzing the entire resource, reducing overall processing time while maintaining high user satisfaction through topic-relevant content placement
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for distributing content based on context are disclosed. In one aspect, a method includes identifying, in a single resource, multiple different content item slots that are available for presentation of multiple different content items. A determination is made that a first content item slot is located in a first portion of the single resource, and that a second content item slot is located in a second different portion of the resource. A first content item is selected for presentation in the first content item slot based on terms that correspond to a first topic of the first portion of the resource. A second content item is selected for presentation in the second content item slot based on terms that correspond to a second topic of the second portion of the resource.