Database Search Using Segmented Taxonomy Tables
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for navigating and exploring large, hierarchically structured databases with complex taxonomies are inefficient, especially when dealing with a high number of digital information contents, as they struggle to handle multiple classifications and composed concepts effectively.
Innovation Solution
A method involving the creation of data table structures within a data processing system that allows for efficient searching by generating data tables based on content, taxonomy, and classification tables, using hash functions to convert search strings into indices for retrieving relevant data, enabling efficient classification and content queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional navigation methods are used to explore large hierarchically structured databases, then the system can handle complex taxonomies with multiple classifications, but the exploration efficiency and retrieval speed deteriorate significantly
Solution Approach 1:
The patent segments the complex taxonomy structure into multiple independent dimension tables (e.g., genre dimension, production dimension, distributor dimension). Each dimension table contains concepts at different levels of abstraction and their relationships, allowing the system to handle complex taxonomies by dividing them into manageable, independent segments that can be queried efficiently without processing the entire complex structure.
Solution Approach 2:
The patent introduces an intermediary indexing mechanism that maps between search terms and the segmented dimension tables. This intermediary layer translates user queries into efficient table lookups, mediating between the complex taxonomy structure and the retrieval process, thereby improving exploration efficiency without requiring direct navigation through the complex hierarchy.
2Adaptability or versatility
If the database includes a high number of digital information contents with multiple classifications, then the classification capability is improved, but the time required for content retrieval and exploration increases
Solution Approach 1:
The patent segments content into multiple independent classification dimensions (genre, production, distributor, etc.), where each dimension can be queried separately. This allows the system to maintain high classification capability by supporting multiple independent classification schemes while reducing retrieval time by enabling targeted queries on specific dimensions rather than searching through all classifications simultaneously.
Solution Approach 2:
The patent performs preliminary organization of content into structured dimension tables during the database setup phase. Concepts, their hierarchical relationships, and content associations are pre-organized into normalized tables with clear schemas. This preliminary structuring enables efficient retrieval operations later, as the system doesn't need to process complex classification relationships in real-time but can perform direct table lookups.
3Measurement precision
If exact search paradigm is used with specific query terms, then retrieval precision is improved, but the system fails to assist users who do not know precisely what they are looking for
Solution Approach 1:
The patent creates a universal search system that handles both exact search and exploratory search through the same dimension table structure. The segmented dimension tables can serve multiple functions: precise filtering when users know what they want, and guided exploration when users need assistance. The same infrastructure supports both paradigms, making the system versatile without requiring separate mechanisms.
Solution Approach 2:
The patent enables dynamic query formulation by allowing users to start with broad dimension filters and progressively refine their search. The system dynamically adapts to user needs by supporting both specific targeted queries and broader exploratory queries on the same dimension tables, transitioning between exact search and exploration modes based on user interaction rather than requiring a fixed search paradigm.
4Stability of the object's composition
If the database is structured with detailed hierarchical taxonomies, then the organization of digital information contents is improved, but the complexity of navigating and exploring the database increases
Solution Approach 1:
The patent segments the detailed hierarchical taxonomy into multiple independent dimension tables, each representing a specific organizational aspect (genre hierarchy, production hierarchy, etc.). This segmentation maintains the stable organizational structure of detailed taxonomies while reducing navigation complexity by allowing users to explore each dimension independently rather than navigating a single complex interconnected hierarchy.
Solution Approach 2:
The patent transforms the traditional single-dimensional hierarchical navigation into a multi-dimensional table structure. Instead of navigating down a single taxonomy tree, users can explore information across multiple independent dimensions (genre, production, distributor, year, etc.), each represented as a separate table. This dimensional transformation maintains comprehensive organization while simplifying navigation by allowing independent exploration of each dimension.
Data Source
AI summary
A method for carrying out searches in a database by means of a data processing system is provided. The database includes a first plurality of first data items and a second plurality of second data items, a generic first data item being in relationship with one or more second data items and vice versa. In an internal memory of the data processing system, at least one among a first and a second data table structure are generated, each one including: a first and a second data table, each comprising a plurality of elements, each one corresponding to a respective first, respectively second, data item and univocally identified by a respective first, respectively second, index. The first and second data tables include a third data table including a plurality of elements, each one in a univocal relationship with a respective element of the first and second data tables.