Hierarchical User Interest Profile Generation for Document Prioritization
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Solution Overview
Problem
Systems that provide users with access to large volumes of documents face challenges in selecting and prioritizing documents for display, as users' attention and time are limited, and existing methods struggle to accurately predict user interest in documents.
Innovation Solution
A profiling system that creates a hierarchical topic set and monitors user interest to generate an interest profile, determining a measure of topical interest for users at various topic levels, which is used to predict user interest in documents and prioritize their display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a large volume of documents is provided to users, then the quantity of information available increases, but the difficulty of selecting and prioritizing relevant documents increases
Solution Approach 1:
The patent segments the large volume of documents into hierarchical topic categories (e.g., sports, entertainment, news, business, and subcategories thereof). Documents are organized and presented according to these segmented topics, allowing users to navigate through structured categories rather than overwhelming unsorted lists, thereby resolving the contradiction between providing大量 documents and enabling easy selection of relevant ones
Solution Approach 2:
The patent replaces manual mechanical selection processes with automated electronic classification and ranking systems. The system automatically analyzes document content, assigns topic classifications, and prioritizes documents based on relevance algorithms, substituting human effort with computational processes to manage large document volumes efficiently
2Productivity
If documents are prioritized for display based on predicted user interest, then user engagement improves, but the accuracy of interest prediction is challenging to achieve
Solution Approach 1:
The patent implements feedback mechanisms where the system monitors user interactions with displayed documents (such as clicking, reading time, and navigation patterns) and uses this feedback to continuously refine and update user interest profiles. This iterative feedback loop improves the precision of interest predictions over time, resolving the contradiction between enhancing user engagement and achieving accurate prediction
Solution Approach 2:
The patent changes the parameters used for prediction by maintaining dynamic user profiles that track evolving interests, document readability metrics, and contextual relevance factors. By adjusting and updating these parameters based on accumulating data, the system improves prediction accuracy while maintaining high user engagement
Data Source
AI summary
Profiling systems and methods of creating and using user interest profiles are described. In some example embodiments, the method includes: creating a topic set which includes topics which are organized in a hierarchical structure which includes a plurality of topic levels including an upper topic level and a lower topic level, each topic in the lower topic level being a subtopic of at least one of the topics in the upper topic level; monitoring interest in a plurality of documents for a user to identify one or more documents-of-interest to the user; and based on the monitored interest for the user, creating an interest profile for the user by determining a measure of topical interest for the user for at least one of the topics at the upper topic level and for a subtopic of that topic, the subtopic being at the lower topic level.