Browser Plug-in Inference Engine for Bookmark Tag Suggestions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional tag-based online bookmark systems fail to provide accurate keyword suggestions and are inefficient due to server processing delays, network latency, and lack of user-friendly interfaces for highlighting tags, making the bookmarking process time-consuming and cumbersome.
Innovation Solution
A lightweight inference engine is integrated as a browser plug-in that performs background analysis to suggest highly relevant keywords or tags, displayed in a new transparent window with varying font sizes and colors to indicate importance, reducing server delays and enhancing user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a conventional tag-based online bookmark system is used, then users can store and share bookmarks across platforms, but the system suffers from server processing delays and network latency that slow down the bookmarking process
Solution Approach 1:
The system pre-generates and caches suggested tags on the client side before the user actually bookmarks the page. The inference engine analyzes the web page content in the background and prepares tag suggestions in advance, so when the user clicks to bookmark, the tags are already ready and no server round-trip is needed.
Solution Approach 2:
A lightweight inference engine is introduced as an intermediary component that runs locally in the browser as a plug-in. This engine performs the tag generation function locally rather than requiring server processing, acting as a mediator between the web page content and the bookmarking function.
2Ease of operation
If conventional bookmark systems pop up new windows or redirect to bookmark sites for tag input, then users can enter tags, but the interface becomes cumbersome and user-friendly interaction is reduced
Solution Approach 1:
The tag suggestion interface is merged with the original web page display by rendering the suggested tags as an overlay directly on top of the current page content. This combines the bookmarking function with the browsing function in a single view, eliminating the need to switch windows or redirects.
Solution Approach 2:
The system uses visual styling with different font sizes and colors to highlight and prioritize suggested tags, making the interface more intuitive and easier to use. Important tags are displayed with larger, more prominent styling to guide user selection.
3Loss of information
If conventional systems provide keyword suggestions, then users can get tag ideas, but the suggestions are not accurate enough due to lack of background analysis
Solution Approach 1:
The inference engine acts as an intermediary that performs sophisticated background analysis of the web page content locally. It extracts semantic information from the page and generates accurate tag suggestions without requiring complex server-side processing.
Solution Approach 2:
The system performs self-service by conducting the tag analysis and generation entirely on the client side using the locally-running inference engine. The browser plug-in analyzes the web page content itself and generates suggestions autonomously without needing external server assistance.
Data Source
AI summary
Disclosed are method and a system, as well as a computer program product for providing suggested tags associated with a target web page for manipulation by a user. The preferred embodiment of the present invention is implemented by generating a list of keywords associated with the target web page as suggested tags; adding the keywords as suggested tags into the page and transforming the page bearing the keywords into a HTML file, while the user decides to bookmark the page; and creating a layer of new transparent or semi-transparent window overlaying an original window displaying the page, the transformed page with said keywords being rendered on the new window for displaying the suggestion for said user's manipulation.