Personalized Search Preview Generation for Data Management
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Solution Overview
Problem
Traditional data management systems fail to present search results in a manner that allows users to quickly and accurately identify relevant assistance documents, leading to increased costs and user frustration due to inefficient search processes.
Innovation Solution
The implementation of natural language processing and machine learning techniques to generate personalized previews of assistance documents, tailored to individual users' language styles and attributes, enabling them to quickly determine the relevance of search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional data management systems provide search results as titles only, then the system complexity is low, but users cannot quickly and accurately identify relevant assistance documents
Solution Approach 1:
The system generates personalized previews of assistance documents before users view them. These previews are created in advance based on user attributes and document content, allowing users to quickly assess relevance without reading full documents, thus improving identification accuracy while maintaining reasonable system complexity
Solution Approach 2:
The patent introduces personalized previews as an intermediary element between search query results and full assistance documents. These previews act as a mediator that helps users quickly determine document relevance, reducing the need to read full documents while improving search effectiveness
2Productivity
If traditional systems provide small sample previews of assistance documents, then some relevance information is provided, but users still cannot quickly determine relevance and may perform additional fruitless searches
Solution Approach 1:
The system generates personalized previews that are specifically tailored to each user's attributes, language style, and search context. Instead of providing generic uniform previews, the system adapts the content, length, and style of previews to match individual user needs, making the preview information more relevant and useful for quick assessment
Solution Approach 2:
The patent dynamically adjusts multiple parameters of the preview including length, content selection, language style, and formatting based on user attributes and document characteristics. This parameter optimization allows the preview to convey maximum relevance information in minimal space, improving search efficiency and reducing time spent on additional searches
3Ease of operation
If users cannot quickly find answers, then system resource usage increases due to additional searches and customer support requests, but user experience deteriorates
Solution Approach 1:
The system performs preliminary analysis of assistance documents to generate personalized previews before users view them. This advance preparation includes analyzing document content, identifying key information, and formatting it according to user preferences, so users can immediately assess relevance without requiring additional processing or support interactions
Solution Approach 2:
The personalized preview system enables users to self-assess document relevance without requiring customer support intervention or multiple search attempts. Users can independently determine whether a document answers their question by reviewing the customized preview, reducing the burden on support systems and optimizing resource utilization
Data Source
AI summary
A method and system provides personalized search results to users of a data management system. The method and system receives a search query from a user and generate initial search results including a plurality of assistance documents relevant to the query data. The method and system utilizes natural language analysis and machine learning processes to analyze the query data, user attributes data, and the assistance documents in order to generate personalized previews of the assistance documents for the user. The method and system output personalized search results to the user including the personalized previews of the assistance documents.