Dynamic Search Result Injection via Dwell Score Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional search engines precompute a large set of search results, leading to inefficiencies in displaying relevant results, as users often interact with only the top results, and may abandon searches if not finding helpful content within the first few pages, resulting in a need for improved pagination and user assistance.
Innovation Solution
Implementing a dwell signal to calculate and utilize dwell scores for search results visible in the viewport, which informs the display of related suggested items and influences the generation of subsequent search result pages, allowing for dynamic pagination and reduced precomputation of search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a large set of search results is precomputed and displayed, then users have more options to choose from, but the system complexity and computational resources increase significantly
Solution Approach 1:
The patent divides search results into multiple pages, with each page containing a limited number of results. Instead of precomputing and displaying all results at once, the system computes results page-by-page, reducing the computational burden on each request while maintaining user access to a large total number of results across multiple pages.
Solution Approach 2:
The patent implements dynamic pagination where the system adaptively determines which results to display on subsequent pages based on user interaction patterns. The search result set is not static but dynamically adjusted based on dwell scores and user behavior, allowing the system to maintain versatility while reducing complexity through selective computation.
2Ease of operation
If conventional pagination displays fixed sets of results, then the system is simple to implement, but users may abandon searches if helpful content is not found in the first few pages
Solution Approach 1:
The patent implements feedback mechanisms by tracking user interactions with search results, specifically measuring dwell time on each result. This feedback is used to compute dwell scores that influence the ordering and selection of results on subsequent pages, creating a loop where user behavior directly shapes future result presentations to improve search success rates.
Solution Approach 2:
The patent performs preliminary computation of a reduced set of high-potential search results before presenting them to users. By precomputing and prioritizing the most relevant results based on initial analysis, the system reduces the time users need to spend searching while maintaining simplicity in the pagination implementation.
3Manufacturing precision
If dwell scores are calculated for all search results, then the relevance of subsequent pages is improved, but the computational overhead increases
Solution Approach 1:
The patent applies dwell score calculation selectively rather than uniformly to all search results. The system focuses computational resources on calculating dwell scores for results that are most likely to be relevant based on their position, initial relevance scores, and user interaction patterns. This localized approach improves result relevance while reducing overall computational overhead.
Solution Approach 2:
The patent calculates dwell scores for a subset of search results rather than all results. By computing dwell scores only for the most promising results on each page (those with highest initial relevance or strategic positions), the system achieves improved relevance for subsequent pages while avoiding the excessive computational cost of analyzing every single result.
Data Source
AI summary
Systems and methods inject related content to a search result using a dwell score. For example, a method may include, for at least one result at least partially displayed in a viewport, calculating a dwell score for the result at based on an amount of time the result has been in the viewport and a position of the result in the viewport and, if the dwell score meets a threshold, displaying suggested links for the result in the viewport. Another example method includes displaying a scrollable set of search results in a viewport and, while waiting for a scroll action or link selection, calculating a dwell score for at least one result that has content visible in the viewport and updating ranking signals based on the dwell score. The updated ranking signals are used to generate a next set of search results for the query.