AI Search Result Categorization for Better Intent Matching
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Solution Overview
Problem
Current techniques for providing content to users seeking information are insufficient in orienting users to complex or unfamiliar solution spaces, leading to repeated and complex searches, wastage of processing resources, and user frustration due to inadequate matching of user intent and overly narrowing search results.
Innovation Solution
A computer-implemented method using AI models to generate categories and freeform descriptive text for search queries, incorporating sponsored content options, to present intuitive and concise summaries, with inline or dedicated text links to relevant information resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current search techniques are used to provide content to users, then processing resources are consumed and time is spent, but user understanding of search relevance is insufficient and search complexity increases
Solution Approach 1:
The patent segments search results into distinct categories (e.g., products, services, information) with clear visual differentiation. Each category is presented as a separate section with its own heading and content structure, making it easier for users to understand what type of information they are viewing and reducing search complexity.
Solution Approach 2:
The patent introduces an intermediary layer between the search query and results that generates explanatory text and category labels. This intermediary processing step enhances user understanding by explicitly describing what each result represents and how it relates to the search intent, without significantly increasing overall search complexity.
2Reliability
If current search techniques are used, then search results are provided, but user intent is not accurately matched and repeated searches occur
Solution Approach 1:
The patent implements feedback mechanisms where the system analyzes user interactions with search results (such as clicks, scrolls, and time spent) to refine and adjust category generation and result presentation. This feedback loop improves user intent matching accuracy over time by learning from actual user behavior patterns.
Solution Approach 2:
The patent performs preliminary categorization and analysis of search results before presenting them to users. By pre-organizing results into meaningful categories and generating explanatory text in advance, the system reduces the need for users to perform repeated searches to understand what is available, thereby reducing time loss.
3Productivity
If current search techniques are used, then content is delivered to users, but performance metrics for third party content deteriorate
Solution Approach 1:
The patent applies local quality enhancement by providing tailored category labels and explanatory text specifically for third-party content within the search results. Instead of treating all results uniformly, the system optimizes the presentation and description of sponsored and third-party content to improve its visibility and performance metrics without wasting processing resources on unnecessary operations.
Data Source
AI summary
Systems and methods for providing information responsive to a user search are provided. Such a method includes receiving a search query from a client device and generating a plurality of categories associated with the search query using a first artificial intelligence (AI) model. The method also includes selecting a plurality of sponsored content options that are responsive to the search query and, for each category, generating respective freeform descriptive text for the category using a second AI model. The method also includes causing the client device to present a user interface that includes (i) the respective freeform descriptive text for each category and (ii) links to third party information resources associated with the selected plurality of sponsored content options. An arrangement of the links within the user interface indicates which of the plurality of sponsored content options correspond to which of the plurality of categories.