Intelligent Interface Accelerating Service Provider Discovery
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Solution Overview
Problem
Current systems lack the ability to efficiently classify user activities on client computers to identify searches for service providers and automatically facilitate connections with relevant service providers, leading to suboptimal user experience in finding products and services online.
Innovation Solution
A method that involves obtaining user browsing data, classifying user activities to detect searches for service providers, and performing web crawling to gather research data, which is then used to provide action decisions such as transmitting communication offers to users on behalf of service providers, utilizing predictive models and natural language processing to enhance user interface operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional manual search methods are used, then users have control over their search process, but the time required to find service providers is excessive
Solution Approach 1:
The system performs preliminary actions by proactively monitoring user browsing behavior and pre-classifying search intent before the user completes their search query. When a user is detected to be searching for a service provider, the system automatically initiates web crawling and data collection in advance, so that when the user needs results, they are already prepared and can be presented immediately, significantly reducing search time.
Solution Approach 2:
The system enables self-service by automatically performing the entire search and selection process without requiring user intervention. The browser plugin autonomously monitors browsing data, classifies search intent, crawls relevant websites, extracts information, and presents tailored service provider results based on the user's browsing behavior, eliminating the need for manual search queries and comparisons.
2Loss of information
If web crawling on multiple websites is performed, then comprehensive research data is obtained, but the complexity of the system increases
Solution Approach 1:
The system segments the complex web crawling process into distinct manageable modules: browsing data collection from the browser plugin, search intent classification using machine learning models, web crawling of candidate websites, data extraction and processing, and result presentation. Each module handles a specific aspect of information gathering, making the overall complex task of obtaining comprehensive research data from multiple websites more manageable and maintainable.
Solution Approach 2:
The system introduces an intermediary classification layer that acts as a mediator between raw browsing data and the web crawling process. The machine learning-based intent classification system processes and interprets browsing behavior patterns, translating them into structured search queries that guide the web crawling process. This intermediary layer simplifies the system by providing intelligent routing for data collection based on understood user intent rather than requiring complex direct crawling logic.
3Measurement precision
If user browsing data is monitored and classified, then accurate service provider matching is achieved, but the amount of data processing increases
Solution Approach 1:
The system applies partial action by monitoring and processing only the most relevant browsing data elements necessary for classification rather than analyzing all browsing behavior in detail. The machine learning model is trained to identify key patterns and features in browsing data that are most indicative of search intent, allowing accurate classification without processing every detail of user behavior, thus reducing processing resource consumption while maintaining high classification accuracy.
Data Source
AI summary
Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: obtaining user browsing data from a browser plugin of a client computer device, the client computing device being associated to the user; examining the user browsing data; classifying a current activity of the user in dependence on the examining the user browsing data, wherein the classifying includes classifying the current activity of the user as searching for a service provider; in response to classifying the current activity of the user as searching for a service provider, performing web crawling on multiple websites to obtain research data, wherein the multiple websites are crawled by the performing web crawling in dependence on extracted data extracted by the examining the user browsing data; and providing an action decision in dependence on the research data, wherein the action decision includes a decision to transmit a communication to the user on behalf of a certain service provider.