Web Page Archiving via User Interest Detection
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Solution Overview
Problem
Users face challenges in accessing previously viewed web page data when the original web page no longer exists or has been modified, as existing technologies lack efficient methods for archiving and retrieving such data.
Innovation Solution
A computer-implemented method and system that determines user interest in a web page, archives the web page data along with associated concepts, and provides archived data when a user makes a search request related to the archived content, thereby bypassing the need for explicit bookmarking and manual rediscovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually bookmark web pages, then they can access previously viewed content, but users must explicitly bookmark each page and manually rediscover it later
Solution Approach 1:
The system automatically archives web pages by detecting user interest through browsing behavior analysis, eliminating the need for manual bookmarking. The archiving system serves itself by automatically identifying which pages to archive based on user engagement metrics such as time spent on page, number of visits, and browsing patterns.
Solution Approach 2:
The system performs preliminary archiving of web pages before users need to access them again. By proactively archiving pages based on detected user interest, the system ensures content is preserved and ready for retrieval, bypassing the need for manual bookmarking actions at the time of viewing.
2Reliability
If the original web page is modified or deleted, then users cannot access the original content, but archiving and storing copies requires additional storage resources
Solution Approach 1:
The system applies selective archiving by archiving only those web pages that exhibit characteristics of user interest, rather than archiving all pages uniformly. This localized approach to content preservation reduces overall storage requirements while ensuring that personally relevant content is preserved.
Solution Approach 2:
The system uses parameter-based filtering to determine which pages to archive, changing the state from 'all pages archived' to 'only interested pages archived'. By monitoring parameters such as time spent on page, visit frequency, and interaction patterns, the system dynamically determines archiving eligibility, optimizing storage usage.
3Loss of time
If users search for archived content, then they can retrieve saved web pages, but the search process requires time and effort to locate relevant information
Solution Approach 1:
The system uses feedback from user browsing behavior to automatically tag and categorize archived pages. By analyzing patterns such as which pages users visit frequently or spend significant time on, the system generates metadata and concepts that enable intelligent retrieval, reducing search effort.
Solution Approach 2:
The system replaces manual search mechanics with automated concept-based retrieval. Instead of requiring users to manually search through archived pages, the system uses natural language processing and concept extraction to enable semantic search, substituting mechanical browsing with intelligent automated retrieval.
Data Source
AI summary
Interest of a user in a website is determined. One or more concepts associated with the website are determined. A version of the website is archived.