Group-by Attribute Search Result Organization
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Solution Overview
Problem
Traditional search engines provide one-dimensional search result lists that lack flexibility in relevancy presentation, overwhelming users with unorganized data, even if relevant, due to inadequate grouping of search results by attributes.
Innovation Solution
Implementing a group-by search result system that utilizes attribute values to rank and organize search results, allowing users to control the presentation and formatting through object ranking algorithms and user-selectable attributes, thereby condensing results for efficient processing and display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If search results are presented as a large one-dimensional list according to a single relevancy, then the search engine can return relevant data quickly and efficiently, but the user becomes overwhelmed and dissatisfied with the search results
Solution Approach 1:
The patent segments the one-dimensional search result list into multiple two-dimensional conditional views by grouping results based on different attributes (e.g., date, location, type). This segmentation allows users to view results organized by specific criteria without processing the entire flat list, improving both efficiency and usability.
Solution Approach 2:
The patent transitions from a one-dimensional search result list to a two-dimensional conditional view system. The first dimension represents the traditional relevancy ranking, while the second dimension introduces attribute-based groupings. This dimensional expansion enables users to navigate and filter results more effectively, reducing overwhelming information while maintaining processing efficiency.
2Ease of operation
If search results are grouped by multiple bases of relevancy with user-selectable attributes, then users gain control over relevancy groupings and readability improves, but the complexity of the search result system increases
Solution Approach 1:
The patent implements a dynamic search result system where the grouping and organization of results change based on user-selected attributes. The system adapts its structure by allowing users to dynamically switch between different attribute groupings (e.g., grouping by date, by location, by type) without requiring a new search, thus providing control while managing complexity through flexibility.
Solution Approach 2:
The patent creates a universal search result presentation system that can handle multiple grouping criteria and attribute types within a single framework. The two-dimensional conditional view structure serves multiple functions: it can group by any attribute, maintain relevancy ranking, and allow user customization, thereby providing control without proportionally increasing system complexity.
3Ease of operation
If attribute values are used to further group search results based on attribute value relevancy, then search results can be organized by multiple criteria improving readability, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary grouping of search results by attributes before final presentation. The system pre-processes results into attribute-based groups and maintains these groupings for quick user access. This preliminary organization reduces the need for real-time processing when users switch between different view conditions, thereby improving readability while minimizing additional processing time.
Data Source
AI summary
Search results are ranked by applying sub-relevancies within a search result list. This permits search result lists to be further refined into more manageable relevant groupings from a user's perspective. The sub-relevancies or ‘group-by’ parameters are derived from search result attributes. Attribute values from the attributes are employed in a ranking scheme to group the search results based on attribute value relevancy. The grouped search results can then be displayed to users via a search result page. In one instance users can select which attribute value is used to group the search result list. Ranking processes are based on object ranking algorithms that consider each attribute value as an object type. Some instances provide for search result list group condensing based on relevancy of the attribute values as well. A top-k instance can be employed to limit the search results to control the amount of time required for processing groupings.