Shopping List Interface for Parsing Unstructured Product Inputs
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Solution Overview
Problem
Electronic list systems face challenges with sporadic, generalized, and poorly-focused user inputs, particularly in electronic commerce, where inputs often mix product descriptions, prices, sources, and brands without a clear order, and lack methods to reconcile these differences.
Innovation Solution
The technology employs a list system that parses user inputs for a minimum set of product data, queries shopping services, and presents organized product descriptions with hierarchical organization, allowing users to select and order items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system accepts unstructured user inputs (mixing product descriptions, prices, sources, and brands), then the system captures more user intent information, but the input parsing becomes more difficult and requires more complex processing
Solution Approach 1:
The patent segments the user input into distinct entities (product descriptions, prices, sources, brands) using named entity recognition and classification. This allows the system to handle diverse, unstructured inputs by breaking them down into manageable components that can be processed independently through standardized parsing rules for each entity type.
Solution Approach 2:
The patent introduces an intermediary parsing layer that sits between the raw unstructured user input and the structured query generation. This intermediary component uses natural language processing techniques to mediate the transformation from messy user input to clean, structured query parameters, absorbing the complexity in this dedicated layer.
2Measurement precision
If the system requires highly-specific product descriptions for shopping services, then the query accuracy improves, but the ease of operation decreases due to the difficulty of providing precise inputs
Solution Approach 1:
The patent implements self-service by having the system automatically extract and generate the required specific product descriptions from the user's initial unstructured input. Instead of requiring users to manually provide precise product descriptions, the system serves itself by inferring and generating the necessary query parameters from broader user input statements.
Solution Approach 2:
The patent performs preliminary action by pre-processing and structuring the user input before it reaches the shopping service query generation. The system performs initial parsing, entity extraction, and query construction as preliminary steps, so that when the shopping service receives the query, it already has the highly-specific product descriptions needed for accurate results.
3Quantity of substance
If the system processes multiple types of data (product genus, subgenus, name, brand, price, retailer, manufacturer, size, quantity), then the query comprehensiveness improves, but the parsing time and processing resources increase
Solution Approach 1:
The patent applies partial action by implementing selective parsing based on the user input and shopping service requirements. Rather than always parsing all possible data types, the system parses only the necessary fields based on what is provided in the user input and what the shopping service needs, reducing unnecessary processing time while still extracting comprehensive data when available.
Solution Approach 2:
The patent uses parameter changes by dynamically adjusting the parsing depth and scope based on the complexity of the user input and the specific shopping service being queried. The system changes parsing parameters such as the level of detail extracted and the number of data fields processed to match the actual requirements of each query scenario.
4Shape
If the system presents product descriptions in a hierarchical organization, then the information structure improves, but the device complexity increases
Solution Approach 1:
The patent segments the product information into hierarchical levels (product genus, subgenus, specific product details) and presents them in a structured tree-like format. This segmentation allows complex product information to be organized into manageable hierarchical categories that are easier to navigate and understand, breaking down the information structure into logical segments.
Data Source
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AI summary
Processing inputs to electronic list systems. Receiving, from a user device, a user input. Parsing the received user input for a minimum set of product data for querying a shopping service. Upon parsing a minimum set of product data for querying a shopping service, querying at least one shopping service using the parsed data. Receiving, from at least one queried shopping service, at least one product description responsive to the query. Presenting, via the user device, each received at least one product description to the user.