Inverted Index Database To Operator for Hierarchical Query Precision
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Solution Overview
Problem
Inverted Index Databases (IIDBs) like Lucene are limited in representing structural relationships between records beyond single-level linear collections, making it difficult to perform precise searches for ambiguous terms such as consumer brand names in large-scale databases.
Innovation Solution
The introduction of a 'To' operator in IIDBs allows for intra-cluster level conversion, enabling efficient representation of hierarchical relationships between records and the use of bit maps to preserve structural information, facilitating more precise query formulation and exclusion of irrelevant results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional inverted index databases are used for searching, then search speed is maintained, but the ability to represent hierarchical relationships between records is limited
Solution Approach 1:
The patent implements nested bit maps where bit maps are organized in a hierarchical structure corresponding to the nested doll pattern. Each level of the hierarchy has its own bit map that represents records at that level, allowing efficient representation of hierarchical relationships while maintaining the inverted index structure. This enables the database to represent complex hierarchical relationships between records without fundamentally changing the underlying inverted index architecture.
2Measurement precision
If hierarchical structure is added to represent complex relationships, then query precision for ambiguous terms improves, but the complexity of the database structure increases
Solution Approach 1:
The patent adds a hierarchical dimension to the traditional flat inverted index structure by organizing bit maps across multiple levels. This dimensional transformation allows queries to operate on ambiguous terms with greater precision by leveraging the hierarchical context, while the bit map structure efficiently manages the increased complexity through compact binary representations.
3Measurement precision
If bit maps are used to preserve structural information, then query accuracy improves, but memory usage increases
Solution Approach 1:
The patent changes the representation parameter from traditional pointer-based or keyword-based structures to compact bit maps. This parameter change dramatically reduces the space required to represent structural information while maintaining query accuracy, as bit maps use binary digits to efficiently encode presence/absence information at each hierarchical level.
Data Source
AI summary
To the standard operations of an inverted index database, a new “To” operator is added. The “To” operator treats the standard single-level linear collection of records as being organized into localized clusters. Techniques for hierarchical clusters are presented. During indexing, hierarchical clusters are serialized according to a uniform visitation procedure. Serialization produces bit maps, one for each hierarchical level, that preserve the hierarchical level of each record and its location in the serialization sequence. The “To” operator accepts a list of records, each at a same hierarchical level in a cluster, and a specification of a hierarchical level that all the input records should be converted into. The “To” operator outputs a list of records, representing a conversion of the input records to the specified new level.When searching a Corpus-of-Interest for an Object-of-Interest, techniques are presented for greatly improving the process by which Exclude Terms are identified. Exclude Terms are particularly useful when the lexical units, representing an Object-of-Interest, are ambiguous. When in the mode of searching for Exclude Terms, the Object-of-Interest of interest is sought, in the Corpus-of-Interest, in a broader context than when the Exclude Terms are utilized as part of an actual query. The Object-of-Interest can match anywhere in a snippet, rather than just in the focus sentence. Using the “To” operator, the focus sentences thus found are converted into role values. Statistical sampling of the role values may be used to reduce the data for the next step of processing. The role values are subjected to frequency and cluster analysis, at the lexical unit level, in order to identify candidate Exclude Terms that a user can select. Frequency and clustering information, is presented to the user, to aid in the decision process. The search for Exclude Terms can be repeated, using the Exclude Terms located thus far.