Interactive Search Engine for Deep Decision Queries
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Solution Overview
Problem
Conventional search engines fail to provide precise results for deep decision-type queries due to limited comprehensive ability, requiring user intervention and lacking individualized services.
Innovation Solution
An interactive searching method and system that analyzes user queries to determine if they belong to a deep decision type, providing an interactive region for inputting additional information, allowing for intelligent interaction and precise result retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional search engine returns search results based on correlation with search term, then search results can be provided quickly, but search precision for deep decision-type queries is insufficient
Solution Approach 1:
The patent introduces an interactive feedback mechanism where the search engine engages users in multi-turn dialogue to clarify and refine their search intentions. The system provides preliminary search results, receives user feedback through the interaction region, and iteratively improves result precision based on user responses, effectively resolving the contradiction between quick result provision and search precision.
Solution Approach 2:
The patent performs preliminary analysis of search queries to identify deep decision-type questions before executing the full search. By pre-classifying queries and preparing interactive templates in advance, the system can quickly determine when interactive refinement is needed, maintaining productivity while enabling precision improvement through user interaction.
2Adaptability or versatility
If conventional search engine provides general search results, then service coverage is broad, but individualized service capability is lacking
Solution Approach 1:
The patent dynamically adapts the search service based on user characteristics and query types. The system adjusts its interaction mode, template selection, and result presentation according to the specific user and their deep decision-type query, transforming a static general search engine into a dynamic individualized service system that maintains broad coverage while providing personalized assistance.
Solution Approach 2:
The patent applies different service qualities to different users and query types. For deep decision-type queries, the system provides enhanced interactive refinement capabilities, while for simple queries, it maintains standard search functionality. This localized quality enhancement ensures individualized service where needed without compromising overall service coverage.
3Measurement precision
If interactive region is displayed for deep decision-type queries, then search requirement accuracy improves, but interface complexity increases
Solution Approach 1:
The patent segments the user interface by displaying the interactive region only for deep decision-type queries rather than all queries. This conditional segmentation allows the system to provide enhanced accuracy features only when needed, avoiding unnecessary interface complexity for simple searches while maintaining high precision for complex decision-making queries.
Data Source
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AI summary
An interactive searching method and an interactive searching apparatus are provided. The interactive searching method includes: obtaining by a search engine a first query; obtaining by the search engine a first parsing result of the first query; and obtaining a first search result associated with the first query according to the first parsing result and returning the first search result by the search engine