Nested Topic Indexing for Targeted Information Retrieval
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Solution Overview
Problem
Existing search engines provide numerous documents for a single query, making it difficult for users to find desired information, fail to display hidden information, and lack linkage between users and IoT devices, leading to inefficient information retrieval and increased backend processing.
Innovation Solution
A system and method for retrieving information through topical arrangements, involving user registration, structure creation, query processing, and information retrieval, which includes customizable topic structures, AI-driven query handling, and inverted indexing to segregate and rank information based on user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If existing search engines provide numerous documents for a single query, then the quantity of information is increased, but the difficulty for users to find desired information increases
Solution Approach 1:
The patent segments the information retrieval process by introducing multiple specialized search engines, each dedicated to a specific topic category (e.g., health, education, technology). Each search engine processes queries within its domain and returns results organized by subcategories, thereby segmenting the overwhelming volume of information into manageable, topic-specific portions that are easier for users to navigate.
Solution Approach 2:
The patent introduces a central portal or interface that acts as an intermediary between the user and multiple specialized search engines. This intermediary receives the user's query, determines the relevant topic categories, distributes the query to appropriate specialized search engines, aggregates their results, and presents them in an organized manner, thereby mediating the interaction and reducing user burden.
2Ease of operation
If existing search engines retrieve search results based on user query and apply criterion to present results in clusters, then the organization of information is improved, but the search output is limited only to category structures
Solution Approach 1:
The patent implements dynamic search capabilities where the output format and organization can adapt based on user preferences and query characteristics. Each specialized search engine can present results in multiple formats (detailed views, summaries, lists, graphical representations) and users can dynamically switch between these formats. The system also dynamically adjusts the level of detail and categorization based on the query type and user interaction patterns.
3Quantity of substance
If the search engine searches on huge information, then the comprehensiveness of search results is improved, but the backend processing power increases
Solution Approach 1:
The patent segments the backend processing load by distributing it across multiple specialized search engines, each handling a specific topic category. Instead of one monolithic search engine processing all queries across all domains, the system divides the information space and processing responsibilities into independent modular units. Each specialized engine maintains its own optimized index and processing pipeline for its domain, reducing the processing power required for each individual query while maintaining comprehensive coverage across all topics.
Data Source
AI summary
A system and method for retrieving information through topical arrangements includes registering one or more users on a platform, receiving different types of nested topics and different types of information, creating different structures of the types of topics with nested levels, networking graphically these types of topics levels, arranging topics to retrieve information through these arrangements, receiving a query from one or more users or Internet of Things, creating an document list and full inverted index on these types of topics levels, extracting a plurality of tokens from the query, matching the plurality of tokens extracted from the query, mapping a plurality of matched topic levels with a higher-level set, retrieving these types of topics levels and information from a plurality of databases, segregating different types of topics and information, ranking sequence for a plurality of retrieved topics, displaying as per segregation of various topics in terms of category.