Image Search Intent Guidance With First-Reply Recommendations
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Solution Overview
Problem
Conventional image recognition and AI dialog products lack effective guidance for unclear user requirements, fail to understand new functions, and cannot respond to extended user needs, leading to inefficient and unsatisfactory search experiences.
Innovation Solution
An image-based search processing method that determines a user's original search intent from an image, generates a search result and recommended content, and outputs them together in the first round of reply, simplifying the search flow and enhancing user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the user needs to clarify requirements or re-take a photo when search results do not meet expectations, then the search can be refined, but the search complexity increases and efficiency decreases
Solution Approach 1:
The system performs preliminary analysis of the uploaded image to generate multiple potential search results and recommended search terms before the user even submits their query. This preliminary action includes identifying objects, scenes, and attributes in the image, and preparing corresponding search results and recommended terms in advance, so when the user needs refinement, they can directly select from pre-prepared options rather than re-uploading or manually refining their query
Solution Approach 2:
The system provides feedback to the user in the form of recommended search terms and multiple potential search results based on the initial image analysis. This feedback mechanism allows users to see what the system has identified and to easily refine their search by selecting from recommended terms or alternative results, rather than having to restart the search process
2Measurement precision
If the user needs to clarify requirements or re-take a photo when search results do not meet expectations, then the search can be refined, but the time consumption increases
Solution Approach 1:
The system performs preliminary analysis of the uploaded image to generate multiple potential search results and recommended search terms before the user even submits their query. This preliminary action includes identifying objects, scenes, and attributes in the image, and preparing corresponding search results and recommended terms in advance, so when the user needs refinement, they can directly select from pre-prepared options rather than re-uploading or manually refining their query
Solution Approach 2:
The system automatically analyzes the uploaded image and generates recommended search terms and multiple potential search results without requiring user intervention. This self-service capability allows the system to proactively provide refined search options based on its analysis, reducing the time users would otherwise spend manually refining their search queries or re-uploading images
3Adaptability or versatility
If traditional image search only provides search results without recommended content, then the interface is simple, but the user experience and personalization are limited
Solution Approach 1:
The system segments the search result presentation into distinct components: basic search results and recommended search content. This segmentation allows the interface to display multiple types of information in an organized manner, with recommended terms appearing as separate actionable elements that users can select to refine their search, rather than mixing all information together in a cluttered interface
Solution Approach 2:
The system introduces recommended search terms as an intermediary element between the initial image upload and the final search results. These recommended terms act as a bridge, offering users guided refinement options based on system analysis, which helps users navigate from their initial (possibly vague) search intent to more precise results without requiring them to manually formulate refined queries
Data Source
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AI summary
The present disclosure provides an image-based search processing method and apparatus, a device and a storage medium, relating to the technical fields of computer vision, deep learning, natural language processing, and searching. The method includes: determining (S101), in response to receiving an image sent by a terminal, a first requirement corresponding to the image, the first requirement including an original search intent of a user; generating (S102) a search result and a recommended content corresponding to the image according to the first requirement in a case where the first requirement meets a recommendation triggering condition; and returning (S103) the search result and the recommended content to the terminal to cause the terminal to output the search result and the recommended content on a search result page.