Search Result Ranking Using User Affinity Measures
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Solution Overview
Problem
Current search systems fail to effectively prioritize search results based on user affinity and interaction ease, leading to suboptimal user experience in accessing media content.
Innovation Solution
A method that determines an effectiveness measure for each resource by considering user affinity and the number of steps required to access media content, ranking resources accordingly and presenting search results with higher effectiveness measures more prominently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If search results are ranked using traditional relevance scoring, then resources matching the query are identified, but user experience is suboptimal due to lack of prioritization based on user affinity and interaction ease
Solution Approach 1:
The system performs preliminary analysis of user affinity for publishers and pre-calculates effectiveness measures for resources before the user actually searches. User affinity data is collected and stored in advance, allowing the search system to quickly retrieve and apply pre-computed effectiveness measures rather than calculating them in real-time during search execution.
Solution Approach 2:
The system implements feedback loops where user interactions with search results and media content are continuously monitored. This feedback is used to update user affinity measures for different publishers, which in turn updates the effectiveness measures for resources. The refined effectiveness measures then improve future search result rankings, creating a continuous improvement cycle based on actual user behavior.
2Loss of time
If multiple resources are provided without ranking, then comprehensive search results are given, but user time is wasted navigating through less relevant resources
Solution Approach 1:
The system changes the ranking parameter from traditional relevance scoring to an effectiveness measure that incorporates user affinity and interaction ease. By transforming the sorting criterion from simple text-matching scores to composite effectiveness scores that factor in user preferences and publisher affinity, the system reorders resources to prioritize those most likely to satisfy the user's needs based on their demonstrated preferences and interaction patterns.
3Ease of operation
If resources requiring more user interactions are ranked higher, then comprehensive resources are prioritized, but ease of operation decreases due to additional steps required
Solution Approach 1:
The system performs preliminary analysis of user affinity for publishers and pre-calculates effectiveness measures for resources before the user actually searches. User affinity data is collected and stored in advance, allowing the search system to quickly retrieve and apply pre-computed effectiveness measures rather than calculating them in real-time during search execution.
Solution Approach 2:
The system changes the ranking parameter from traditional relevance scoring to an effectiveness measure that incorporates user affinity and interaction ease. By transforming the sorting criterion from simple text-matching scores to composite effectiveness scores that factor in user preferences and publisher affinity, the system reorders resources to prioritize those most likely to satisfy the user's needs based on their demonstrated preferences and interaction patterns.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing ranked search results responsive to a query. In one aspect, a method includes receiving, from a user device, a query specifying an entity, determining two or more resources each of which provide media content related to the entity, for each of the resources, determining an effectiveness measure that is a measure of the effectiveness of the resource to present, to a user of the user device, the media content related to the entity, ranking the resources using, at least in part, the respective effectiveness measure, and providing, to the user device, a presentation of search results for the ranked resources.