Search Query Popularity Scoring and Targeted Ad Display
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Solution Overview
Problem
Current search systems lack the ability to provide users with real-time popularity trends of search results, making it difficult for users to gauge the relevance and validity of recommendations based on recent search behavior, and for service providers to derive optimal advertising rates based on search query popularity.
Innovation Solution
A system and method that assigns a popularity score to search results based on factors like recent search frequency, sales, and revenue, displaying this information alongside search results, and using it to determine when to show targeted advertisements, particularly for items like restaurants, movies, and automobiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If search results are displayed without popularity information, then the search system remains simple and fast, but users cannot gauge the relevance and validity of recommendations based on recent search behavior
Solution Approach 1:
The system pre-calculates and stores popularity scores for search results based on factors like recent search frequency, sales data, and revenue metrics. This preliminary computation allows popularity information to be readily available when users perform searches, eliminating the need for complex real-time analysis while providing comprehensive popularity data.
Solution Approach 2:
A popularity scoring mechanism acts as an intermediary between the search query system and the user interface. This intermediary component processes search result data and generates popularity scores that are then displayed alongside search results, separating the complexity of popularity analysis from both the search engine core and the user interface.
2Reliability
If popularity information is collected and displayed for all search results, then users gain comprehensive decision-making data, but the system requires significant data processing and storage resources
Solution Approach 1:
The system applies different levels of popularity information display based on local conditions - displaying detailed popularity data for certain types of search results while providing simplified or no popularity information for others. This selective approach provides users with relevant decision-making data without processing and storing excessive information for all possible search results.
Solution Approach 2:
The system dynamically adjusts popularity scoring parameters based on the specific context of each search, such as changing which factors (search frequency, sales, revenue) are weighted more heavily depending on the query type and user profile. This parameter adaptation reduces unnecessary data processing by focusing computational resources on the most relevant popularity metrics for each situation.
3Productivity
If targeted advertisements are displayed based on popularity scores, then service providers can derive optimal advertising rates, but the system requires complex scoring and threshold evaluation mechanisms
Solution Approach 1:
The system implements a tiered advertising display approach where popularity scores are calculated for all search results, but targeted advertisements are only displayed for results exceeding certain popularity thresholds. This partial application of the advertising mechanism provides revenue optimization opportunities without requiring complex evaluation for every single search result, reducing overall system complexity.
Solution Approach 2:
The system pre-establishes popularity thresholds and advertising rate structures before processing search queries. By having these evaluation criteria predetermined, the system can quickly determine whether to display targeted advertisements without performing complex real-time evaluations, simplifying the advertising decision-making process while maintaining revenue optimization capabilities.
Data Source
AI summary
A method of indicating the popularity of the subject of a search query comprising receiving a search query from a user, the search query being received by a search server; determining whether the search query is likely to be related to a particular thing; obtaining popularity information for the particular thing; and, transmitting an indicator of the popularity information to a user computer for display. Some embodiments may also include targeted information about the search query subject, including a map showing the search query subject's location, the location of similar things in the same region as the search query subject, one or more advertisements, and the like. The targeted information and/or the popularity information indicator may be displayed with, or separate from search results associated with the search query.