Vortex Searching Index Intersection Optimization
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Solution Overview
Problem
Traditional search engines require significant processing power due to dense index entries and inefficient searching methods, particularly when dealing with Boolean operations and alphabetically ordered indexes, which leads to increased computational complexity.
Innovation Solution
The method involves optimizing search efficiency by selecting parameter patterns that occur less frequently in the data store first, using hashing and speed-up data structures like offset correlation tables to reduce the number of comparisons, and employing abbreviated indexing techniques to eliminate unnecessary searches, thereby minimizing the number of records to be processed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional indexes are used with Boolean operations, then search completeness is improved, but processing power requirements increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing intersection points of parameter patterns in an index data structure. Instead of performing Boolean operations on all records during search, the system has already identified and stored the intersection points beforehand, allowing for rapid retrieval without requiring extensive processing power during actual search operations.
Solution Approach 2:
The patent introduces an intermediary index structure that stores pre-computed intersection points of parameter patterns. This intermediary structure acts as a mediator between the search query and the actual data records, allowing the system to retrieve results by looking up intersection points in the index rather than performing comprehensive Boolean operations on all records, thereby reducing processing power requirements.
2Ease of manufacture
If alphabetically ordered indexes are used, then search organization is improved, but search efficiency deteriorates when dealing with dense entries
Solution Approach 1:
The patent applies parameter changes by transforming the index organization from traditional alphabetical ordering to an ordering based on parameter pattern intersections. Instead of organizing entries alphabetically, the system organizes the index by pre-computed intersection points of parameter patterns, which allows for more efficient searching by directly accessing relevant records without traversing through dense alphabetical entries.
Solution Approach 2:
The patent segments the index into distinct parameter pattern entries with their corresponding intersection points stored in the index data structure. This segmentation allows the system to handle each parameter pattern independently and retrieve only the relevant intersection points for a given query, improving search efficiency by avoiding the need to process dense alphabetical entries.
3Reliability
If all records are searched using traditional methods, then search thoroughness is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-identifying and storing intersection points of parameter patterns in the index before actual search operations. This preliminary computation allows the system to retrieve thorough search results by simply looking up pre-computed intersection points rather than performing complex Boolean operations on all records during search, thereby reducing computational complexity while maintaining search thoroughness.
Solution Approach 2:
The patent creates a copy of the essential search information by storing pre-computed intersection points in the index data structure. Instead of working with all original records and performing complex operations on them, the system uses this copied information (intersection points) to retrieve results, significantly reducing computational complexity while maintaining the thoroughness of the search.
Data Source
AI summary
Determining intersection points of parameter patterns. Parameter patterns are specified in a query. A method includes identifying a first parameter pattern from the query as occurring less often in the index than one other parameter pattern in the query. The data store is searched until a present location of the data store has been identified as including the first parameter pattern. Then the data store is searched for a location of another parameter pattern. If the present location is identified as including the another parameter pattern, then an indication is provided identifying an intersection. Otherwise, the method includes continuing searching remaining portions of the data store to find a location of the another parameter pattern at a new present location. At least one of the acts of searching above includes eliminating at least a portion of records of the data store from searching without being searched prior to being eliminated.