Query Dimension Extraction from Search Results
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Solution Overview
Problem
Traditional web search engines often provide noisy and lengthy search results, making it difficult for users to find the desired information.
Innovation Solution
Extracting and mining query dimensions from search results, which are sets of items that summarize aspects of a query, to help users understand their search results better and guide subsequent searches by weighting, clustering, and ranking these dimensions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional search engines provide comprehensive search results, then the quantity of information is improved, but the noise and lengthiness make it difficult for users to find desired information
Solution Approach 1:
The patent extracts query dimensions from search results by identifying and separating key aspects (such as entities, attributes, and relationships) from the comprehensive result set. This extraction process isolates the most relevant information elements, presenting them in a structured format that helps users quickly understand the search landscape without being overwhelmed by the full volume of results.
Solution Approach 2:
The patent segments the comprehensive search results into distinct query dimensions, each representing a specific aspect of the search topic. By dividing the monolithic result set into organized categories and dimensions, users can navigate and explore information more efficiently, focusing on specific aspects of interest rather than sifting through all results uniformly.
2Reliability
If search results include all relevant documents, then completeness is improved, but the results become noisy and lengthy
Solution Approach 1:
The patent introduces query dimensions as an intermediary layer between the comprehensive search results and the user. These dimensions act as a mediating structure that organizes and contextualizes the complete result set, preserving all relevant information while presenting it in a clearer, more manageable format that reduces noise and improves information clarity.
3Loss of information
If users browse multiple search result pages to understand query aspects, then information completeness is improved, but time consumption increases
Solution Approach 1:
The patent performs preliminary action by pre-extracting and organizing query dimensions from the search results before user interaction. This advance processing creates a structured overview of the search landscape, allowing users to immediately grasp key aspects and make informed decisions about which results to explore further, thereby significantly reducing the time needed to understand query results while maintaining information completeness.
Data Source
AI summary
Techniques are described for automatically mining query dimensions from web pages resulting from execution of a search query. Lists of items such as words, terms, or phrases are extracted from the web pages based on the recognition of free text, metadata tag, or repeated region patterns within the web page text. Extracted item lists are weighted according to document matching and/or inverse document frequency, and item lists are clustered based on shared or similar items within the lists to generate query dimensions. The generated query dimensions, and the items within each query dimension, are ranked according to quality, and high-quality query dimensions are provided for display alongside top search results.