Virtual Agent for Listing Platform Query Response
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Solution Overview
Problem
Existing network sites face challenges in returning up-to-date results for complex queries and navigating vast content arrays, leading to delays and inaccurate results, which consume significant computational resources.
Innovation Solution
Implementing a communication session system that allows users to interact with a smart virtual agent in real time, using a first machine learning model to analyze user profiles and predict relevant information, which is then processed by a generative ML model to generate responsive messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional search and navigation methods are used to handle complex queries and vast content arrays, then comprehensive search capabilities are provided, but computational resource consumption increases significantly and response time delays occur
Solution Approach 1:
The patent introduces a virtual agent as an intermediary between users and the network site content. The virtual agent pre-processes and structures information, maintaining context across interactions, which reduces the computational burden on traditional search systems and accelerates response times for complex queries
2Reliability
If traditional search systems process complex queries with multiple parameters, then comprehensive search results are returned, but computational resource consumption and processing delays increase
Solution Approach 1:
The virtual agent performs preliminary actions by maintaining context and understanding user intent across multiple interactions. This preliminary processing of information reduces the time required to generate accurate search results, as the system does not need to re-process all query parameters from scratch with each interaction
3Adaptability or versatility
If users navigate through vast arrays of content manually, then comprehensive browsing is enabled, but user time and interaction complexity increase
Solution Approach 1:
The virtual agent provides self-service by proactively managing information delivery to users. It maintains context, anticipates user needs, and delivers relevant information without requiring users to manually navigate through vast content arrays, thereby simplifying interactions while maintaining comprehensive browsing capability
Data Source
AI summary
A system is described for allowing a user to communicate with an agent of a listing network platform. The system receives, by a network site, a user interaction in a communication session with an agent of a listing network platform. The system analyzes, by a first machine learning model, a profile associated with the user on the listing network platform to predict a subset of information that is relevant to the user interaction with the communication session. The system combines the subset of information into a prompt and processes the prompt by a generative machine learning model to generate a message that responds to the user interaction. The system, in response to receiving the user interaction, presents the message by the agent of the listing network platform to the user in a user interface of the listing network platform.