Interactive Search Query Clarification via Semantic Knowledge Base
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Solution Overview
Problem
Conventional search engines face challenges in accurately clarifying user search intentions, leading to poor search experiences due to changes in search results when additional keywords are added or existing keywords are modified, resulting in difficulty in obtaining relevant information.
Innovation Solution
An interactive searching method and apparatus that generates intention clarification information using a history search log and semantic knowledge base to display relevant options, allowing users to refine their queries efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the user adds a keyword into the current query or changes a keyword in the current query to perform a further search, then the search results may be more specific, but the search intention of the user may be changed and it becomes difficult to obtain useful information
Solution Approach 1:
The system performs preliminary analysis of the user's query against the semantic knowledge base before executing the search, identifying potential intention clarifications in advance. This allows the system to present clarification options to the user before the search is finalized, preventing loss of original search intention while still enabling accurate search results.
Solution Approach 2:
The system provides feedback to the user by presenting intention clarification information derived from the semantic knowledge base. This feedback loop allows users to review and confirm their search intention before execution, ensuring that the original search goal is maintained while achieving accurate results.
2Ease of operation
If the search engine returns search results sequenced according to their own correlations with the query, then the search results are organized, but the user requirement may not be clarified efficiently
Solution Approach 1:
The system segments the search process into two distinct phases: first organizing search results by correlation (maintaining ease of operation), and second presenting intention clarification information separately (addressing user requirement clarification). This segmentation allows both functions to operate effectively without interfering with each other.
Solution Approach 2:
The semantic knowledge base acts as an intermediary between the query and the search results. It processes the query to generate intention clarification information that bridges the gap between organized results and user requirements, providing additional context without disrupting the organized presentation of results.
3Device complexity
If conventional search engines provide basic search functionality, then the system is simple, but the searching experience of the user is poor
Solution Approach 1:
The semantic knowledge base serves multiple functions: it analyzes queries, generates intention clarifications, and provides context information. This multi-functionality enhances the user experience without requiring separate systems for each function, maintaining reasonable complexity while improving service quality.
Solution Approach 2:
The system automatically generates intention clarification information without requiring user intervention. The semantic knowledge base self-services by autonomously analyzing queries and providing relevant clarifications, improving user experience while adding minimal complexity to the overall system.
Data Source
AI summary
An interactive searching method and apparatus are provided. The interactive searching method includes following steps. A query is obtained, and intention clarification information of the query is generated according to a history search log associated with the query and a predetermined semantic knowledge base to display on a client webpage in which the query is.