App Search Relevance via Connection Keyword Analysis
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Solution Overview
Problem
The proliferation of software applications across various devices has made it challenging for users to efficiently search and access specific apps due to the vast number of options available, leading to irrelevant search results and a suboptimal user experience.
Innovation Solution
A method that determines connections and terms associated with each app, allowing for more relevant search results by analyzing app records, generating result scores, and ranking them based on user queries, thereby selecting and transmitting application download addresses to user devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search methods are used to search for apps, then the search process is simple, but the search results become irrelevant and user experience deteriorates due to the vast number of apps available
Solution Approach 1:
The system performs preliminary actions by pre-determining connections and terms associated with each app before user search queries are received. This allows the search system to have ready-made contextual information about app relationships and functionality, enabling more accurate search results without increasing real-time processing complexity during user interactions
Solution Approach 2:
The system introduces an intermediary layer of connection data and terms that mediates between the user's search query and the actual app records. This intermediary structure enriches search results with contextual information about app connections and associated terms, improving relevance while maintaining a manageable search system architecture
2Adaptability or versatility
If more apps are made available on computing devices, then user functionality and versatility improve, but it becomes increasingly difficult for users to efficiently search and access specific apps
Solution Approach 1:
The system pre-determines connections and terms for each app in advance, building a rich contextual database that enables efficient search. This preliminary preparation allows the system to quickly and accurately match user queries with relevant apps based on pre-computed relationships, maintaining ease of operation even as the number of available apps grows
Solution Approach 2:
The system replaces traditional mechanical search methods with an automated, intelligent search mechanism that uses connection data and terms to automatically identify and rank relevant apps. This substitution eliminates manual browsing through large app lists, maintaining versatility while dramatically improving search efficiency
3Adaptability or versatility
If the number of apps increases across various devices, then the variety of functionality grows, but search results become less accurate and user experience deteriorates
Solution Approach 1:
The system performs preliminary analysis to determine connections and terms for each app before search queries are received. This pre-computed contextual information serves as a reliable foundation for accurate search results, ensuring that even as the number of apps and their functionality varieties increase, search accuracy remains high due to the pre-established relationship data
Data Source
AI summary
Techniques include, for an application (app) record specifying a software app and including an app download address (ADA) for downloading the app, determining connections (e.g., links to and from other resources, such as other apps, APIs, app libraries, and websites) associated with the app and determining terms (e.g., keywords) associated with resources connected with the app by the connections. In some examples, the techniques include receiving a search query from a user device and identifying the record based on (e.g., matches between) the query and the terms. Additionally, or alternatively, the techniques include identifying the record based on the search query, generating a result score for the record based on the terms, and selecting the record from among other records based on the score. The techniques also include selecting the ADA from the record and transmitting the ADA to the user device as search results.