Implicit App Request Detection in Search Systems
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Solution Overview
Problem
Users often fail to find relevant App download options when searching for specific topics due to not using the correct language in their search queries, leading to a lack of interaction with intended business or service providers.
Innovation Solution
A system and method that analyze search queries to identify implicit requests for Apps by associating App IDs with business entity websites, presenting relevant Apps for download, even if the query does not explicitly request them, by stamping URLs with App IDs and determining the relevance based on search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users search for specific topics without using correct App-related language, then they can find general information about the topic, but they fail to find relevant App download options
Solution Approach 1:
The system pre-processes search queries by analyzing their content and intent before users explicitly search for Apps. By detecting topic-related keywords and patterns in general search queries, the system proactively identifies implicit App requests and retrieves relevant App information in advance, presenting it alongside standard search results without requiring users to reformulate their queries.
2Reliability
If the system presents App download options for every search query, then users may find relevant Apps, but it increases the complexity of search results and may overwhelm users
Solution Approach 1:
The system applies different presentation strategies to different search queries based on their content and context. For queries with high probability of implicit App requests, the system prominently displays App download options. For other queries, it maintains the traditional search results format. This localized adaptation ensures App information is presented where most relevant without universally complicating the search interface.
Solution Approach 2:
The system introduces an intermediary analysis layer that sits between the user's search query and the search results. This intermediary component analyzes query intent, determines App relevance, and selectively integrates App information into search results. It acts as a mediator that translates general search queries into targeted App recommendations only when appropriate, maintaining result clarity while improving App discoverability.
Data Source
AI summary
System and methods for presenting users with different App download options in response to certain search queries. In aspects, when a user enters a search query that does not explicitly request an App, systems and methods described herein analyze the results of the search and determine whether the request is an implicit request for Apps. As a result, relevant Apps are identified and presented for download. Other aspects of the present disclosure relate to analyzing and identifying URLs of companies and developers of Apps. Once analyzed and identified, embodiments relate to associating the appropriate URLs with one or more Apps.