User Preference Analysis via Tag Extraction
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Solution Overview
Problem
Existing methods for analyzing user preferences in electronic commerce struggle to quickly and accurately provide customized content due to the inclusion of unnecessary information in web documents, which reduces analysis accuracy and requires separate management by each web server.
Innovation Solution
A user-customized content providing system that collects and analyzes user preference information using anchor tag and form tag information, allowing web servers to request and rank content based on user profiles with weighted keywords, excluding stop words and dynamically updating preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all contents of web documents are analyzed to study user preference, then the analysis comprehensiveness is improved, but the analysis time and computational resources increase significantly
Solution Approach 1:
The patent extracts only the necessary tag information (anchor tags and form tags) from web documents to analyze user preference, rather than analyzing all contents. This extraction approach maintains analysis accuracy by focusing on meaningful user interaction indicators while significantly reducing the volume of data to be processed, thereby resolving the contradiction between comprehensive analysis and analysis time.
2Quantity of substance
If web documents including unnecessary information are analyzed, then the data volume for analysis is improved, but the accuracy of user interest analysis deteriorates
Solution Approach 1:
The patent extracts only relevant tag information (anchor tags and form tags) from web documents, filtering out unnecessary information such as advertisements, company profiles, and copyright information. This selective extraction maintains data volume sufficient for accurate analysis while eliminating noise that would degrade analysis accuracy.
Solution Approach 2:
The patent applies different analysis treatments to different parts of web documents by focusing specifically on tag elements rather than uniform analysis of all content. Anchor tags and form tags are identified as having higher informational value for user preference analysis, so they are extracted and analyzed with higher priority, while other parts are excluded from detailed analysis.
3Device complexity
If user preference information is managed separately by each web server, then the system complexity is reduced, but the ability to provide unified personalized service across multiple servers deteriorates
Solution Approach 1:
The patent implements a centralized user preference management system that serves multiple web servers uniformly. The preference information collected from user interactions is stored centrally and can be accessed by any web server in the system, enabling consistent personalized service across different servers while maintaining manageable system complexity through standardized protocols and data structures.
4Ease of manufacture
If traditional user preference collection methods are used, then the implementation simplicity is improved, but the ability to capture dynamically changing user preferences deteriorates
Solution Approach 1:
The patent implements a feedback mechanism that continuously monitors user interactions with web documents (clicking anchor tags, submitting form tags) and updates user preference information in real-time. This feedback loop enables the system to capture dynamically changing user preferences while maintaining implementation simplicity by leveraging existing web technologies and standardized data collection methods.
Data Source
AI summary
Disclosed are a user-customized content providing device, a method and a recorded medium. In accordance with an embodiment of the present invention, the user-customized content providing device can include a content searching unit, searching a content set related to user's search query word; a user preference information requesting unit, asking an apparatus for user preference information including a user profile and tag information through a network, the user profile including a keyword collected in the apparatus and a point applied with a weight given per keyword; a user preference information collecting unit, receiving the user preference information from the apparatus; a content ranking determining unit, determining a ranking of the content set according to the relation to the user preference information; and a content providing unit, providing the ranked content set to the apparatus.


