Automated Network Browsing Information Collection and Retrieval List Update
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current information retrieval methods rely heavily on user participation and lack initiative, requiring active user input for data updating and screening, leading to inefficient retrieval of relevant information.
Innovation Solution
An information collection method that acquires network browsing information, evaluates it using a scoring algorithm, and generates or updates a retrieval list based on user browsing habits, allowing for automatic data updating and prioritization of relevant websites, which are then searched and pushed to the user through a search engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If keyword-based search engine retrieval is used, then information can be retrieved from large amounts of network information, but the method lacks initiative and relies too much on user participation for automatic data updating and screening
Solution Approach 1:
The system automatically collects browsing information, evaluates it using scoring algorithms, and updates the retrieval list without requiring user intervention. The system serves itself by autonomously performing data collection, evaluation, and list maintenance tasks that previously required active user participation.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring user browsing behavior and using evaluation results to dynamically update the retrieval list. The scoring algorithm processes browsing information and feeds back into list updates, creating a closed-loop system that adapts to user preferences automatically.
2Productivity
If manual bookmarking and retrieval is used, then users can store and access retrieval results at any time, but the process is inefficient and lacks initiative
Solution Approach 1:
The system performs preliminary actions by automatically collecting and evaluating browsing information in real-time, preparing the retrieval list in advance before users need to access it. This eliminates the need for users to manually update bookmarks and reduces the time required for information retrieval.
Solution Approach 2:
The system maintains continuous operation by constantly collecting browsing information, evaluating it, and updating the retrieval list. This continuous automated process replaces间断性 manual bookmarking operations, improving overall productivity and reducing time loss.
3Adaptability or versatility
If automatic evaluation and sorting of browsing information is implemented, then a personalized retrieval list can be generated, but system complexity increases
Solution Approach 1:
The system uses parameter changes by implementing a scoring algorithm that evaluates browsing information based on multiple parameters such as browsing frequency, duration, and user preferences. By changing and weighting different parameters, the system generates personalized retrieval lists without requiring complex artificial intelligence models.
Data Source
AI summary
An information collection method and device are described, the method includes that: network browsing information is acquired; the network browsing information is evaluated; the network browsing information is sorted according to evaluation results; and a network retrieval list is generated or updated according to a sorting result.