Database Search Apparatus Using Ranged Field Buckets for Filter Selection
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Solution Overview
Problem
Conventional search engines face challenges in efficiently retrieving relevant data from large databases due to reliance on user-entered search terms, which can be overly general, leading to irrelevant results and high processing times, especially in applications like audio/visual databases with millions of items.
Innovation Solution
A search apparatus and method that divides database fields into ranged buckets based on attribute values, calculates effectiveness values for each bucket, and provides a graphical representation to help users select top fields as filters for further searches, optimizing search results and reducing processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a conventional search engine performs a recursive search of all metadata to identify items that match a search input, then it can find all relevant items, but it takes a long time (typically over 1 hour) and requires a large amount of processing power
Solution Approach 1:
The patent divides the large database into multiple shards distributed across different servers. Each shard contains a portion of the data and metadata, allowing the search to be performed in parallel across multiple nodes rather than sequentially on a single system, thereby reducing overall search time while maintaining completeness
Solution Approach 2:
The system pre-generates and stores inverted indexes for metadata fields before search operations. These indexes map metadata values to the items that possess them, enabling rapid lookup during search operations without requiring recursive traversal of all metadata during the actual search, thus significantly reducing search time
2Productivity
If a conventional search engine presents search results in relevance order based on generalised search terms, then it can return results quickly, but relevant search results appear far down the list and may be missed by users
Solution Approach 1:
The system introduces an intermediary layer between the user's general search query and the final results. This layer automatically generates and applies refined search filters based on the inverted indexes, acting as a mediator that transforms general queries into more precise searches without requiring user effort, thereby improving result relevance while maintaining speed
Solution Approach 2:
The system incorporates feedback mechanisms that analyze search patterns and user interactions to continuously improve filter generation. By learning from past search behaviors and result relevance, the system refines its automatic filter creation process, ensuring that quickly returned results remain highly relevant to user intent
Data Source
AI summary
A search apparatus (1) coupled to a database, the apparatus (1) comprising: a processor configured to execute instructions; a memory storing instructions which, when executed by the processor, cause the processor to: search the database for items containing a search term, wherein items containing the search term are matched items; identify fields corresponding to attributes of the matched items; define a range of values for each field; divide the range of values for each field into a plurality of ranged field buckets; distribute the matched items between the ranged field buckets based on attributes of the matched items that are within the range of values for each ranged field bucket; calculate an effectiveness value for each field based on the number of matched items in each of the ranged field buckets; select one or more top fields, each top field having an effectiveness value that is greater than a predetermined effectiveness value; and provide an effectiveness indicator output which is indicative of the effectiveness of each top field such that a user can use the effectiveness indicator output to select a top field for use as a filter in a further search.