Natural Language Dialogue Information Retrieval System
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Solution Overview
Problem
Current menu-based systems for voice and chat services are inflexible and require users to navigate through static lists, making it difficult to find specific items in large inventories, especially when users are unsure of the exact item they seek, and do not adapt to user preferences or changes in inventory.
Innovation Solution
An information retrieval system using natural language dialogue that identifies a subset of items from a dynamic inventory based on user input, processes these items to determine relevant classifications, and generates enquiries to help users efficiently find specific items, allowing for iterative refinement of searches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static menu structure is used to organize information, then the system is simple to construct and maintain, but users must navigate through large lists of items and cannot adapt to changing inventories or user preferences
Solution Approach 1:
The patent transforms the static menu structure into a dynamic one that automatically adapts to user inputs and inventory changes. The system generates menu structures on-the-fly based on user preferences and item characteristics, allowing the menu to evolve during interactions rather than remaining fixed. This resolves the contradiction by making the system adaptable without requiring complex manual reconfiguration.
Solution Approach 2:
The system pre-processes inventory data and item characteristics before user interactions to prepare potential menu structures. By analyzing item relationships, categories, and user preferences in advance, the system can quickly generate relevant menu structures when users interact, improving navigation efficiency without adding operational complexity during use.
2Adaptability or versatility
If manual input is used to enumerate menu options, then the system construction is straightforward, but the system cannot handle large inventories or adapt to user preferences automatically
Solution Approach 1:
The system automatically analyzes inventory data and generates menu structures without requiring manual enumeration of options. It extracts relevant information from item data, identifies relationships between items, and constructs appropriate menu hierarchies autonomously. This self-service capability enables the system to handle large inventories and adapt to user preferences while minimizing manual construction effort.
Solution Approach 2:
The patent replaces the mechanical process of manual menu construction with an automated computational system. Instead of manually creating and maintaining menu structures, the system uses algorithms to analyze inventory data, detect patterns, and generate menu structures automatically. This substitution enables handling of large-scale inventories that would be impractical to manage manually.
3Loss of time
If users must navigate through large lists of items to find what they want, then the system maintains a complete inventory, but users spend excessive time searching and may give up before finding relevant items
Solution Approach 1:
The system segments the large inventory into smaller, organized groups based on item characteristics, user preferences, and contextual relationships. By dividing the inventory into meaningful categories and subsets, users can navigate through organized groups rather than browsing through all items sequentially. This segmentation reduces search time while ensuring relevant items remain visible within their appropriate contexts.
Data Source
AI summary
Methods and systems which perform information retrieval using natural language dialogue for navigating an inventory of items are described. One example provides an information retrieval system to a user using natural language dialogue. The system comprises a user input receiving device, an output device, a database comprising an inventory of items, and a processor. The processor is configured to retrieve one or more items from the inventory of items using an iterative process by: in response to receiving from the user input receiving device a user input, identifying a subset of the inventory based on the user input. The processor is configured to automatically process the subset of items to determine a classification for distinguishing between items of the subset, to generate an enquiry for a user using the classification and to transmit the enquiry to the output device. The user input and/or the enquiry may use natural language.