Client-Server Ordering via File-Based Item Extraction
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Solution Overview
Problem
Existing client-server systems for electronic data transactions, such as online shopping, face inefficiencies due to user unfamiliarity with interfaces, varied search term sensitivity, and increased communication and processing burdens, especially for new users, leading to higher abandonment rates and resource consumption.
Innovation Solution
Implementing trained models on the server to process and extract item lists from user-provided files, search for identical or similar items, and automatically add them to an order, reducing the need for manual user interactions and direct search queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional manual search and item selection process is used, then user can find and select items, but communication and processing burden between client and server increases significantly
Solution Approach 1:
The system performs preliminary actions by automatically extracting items from uploaded files (e.g., PDFs, images) and pre-searching for matching items in the database before user interaction. This reduces the number of back-and-forth communications needed during the ordering process.
Solution Approach 2:
The system enables self-service by automatically processing file uploads, extracting item names, performing searches, and presenting results to users without requiring manual client-server interactions for each step, thereby reducing communication overhead.
2Ease of operation
If traditional manual search process is used, then user can search for items, but time taken to familiarize with interface and complete ordering increases
Solution Approach 1:
The system performs preliminary search actions automatically based on extracted item names from uploaded files, presenting search results to users before they need to manually search, thereby reducing both time and interface complexity.
Solution Approach 2:
The system acts as an intermediary by automatically interpreting file contents, translating them into search queries, and presenting matched items to users, eliminating the need for users to directly interact with complex search interfaces.
3Measurement precision
If multiple search terms are tried to return preferred items, then item search accuracy improves, but number of interactions and processing burden increases
Solution Approach 1:
The system performs preliminary processing of file contents to extract accurate item names and automatically generates appropriate search terms, eliminating the need for users to manually try multiple search terms and reducing interaction complexity.
Data Source
AI summary
Certain aspects of the disclosure provide for reducing the number of interactions and/or communications between a client device and server device, and for example, when placing an order on a client and server system for processing user interactions.


