Interest Priority Value Calculation for Document Prioritization
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Solution Overview
Problem
Professionals face difficulties in prioritizing documents from a large collection based on their personal knowledge needs, with existing technologies lacking effective methods to identify high-priority documents and considering social factors in reading choices.
Innovation Solution
A method and apparatus that calculate an interest priority value for each object in a collection, using attributes such as temporal access, document similarity, user relationships, and group membership to determine the relative importance of documents to an individual user, with visual representations to aid in document selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If professionals access information from multiple sources daily, then knowledge base expands, but difficulty in sorting and prioritizing documents increases
Solution Approach 1:
The system automatically calculates interest priority values for documents based on user profiles, access histories, and social contexts without requiring manual sorting by the user. The document selection process serves itself by using algorithmic analysis to prioritize relevant documents, freeing the user from manual organization tasks while maintaining personalized relevance.
Solution Approach 2:
The system transforms document prioritization from a manual process to an automated one by introducing calculated parameters such as interest priority values, access frequency weights, and social context scores. These numerical parameters enable systematic sorting and ranking of documents based on multiple factors including user behavior patterns and professional relevance.
2Ease of operation
If users manually select documents to read, then control over reading choices is maintained, but time consumption increases
Solution Approach 1:
The system performs preliminary analysis of user profiles, access histories, and social contexts before the user needs to select documents. Interest priority values are pre-calculated and stored, allowing the system to immediately present prioritized document lists without requiring the user to perform time-consuming manual sorting or evaluation processes.
3Measurement precision
If the system considers multiple attributes for priority calculation, then document relevance improves, but system complexity increases
Solution Approach 1:
The complex document prioritization task is segmented into distinct calculable components: user profile analysis, access history weighting, social context evaluation, and interest priority value computation. Each component processes specific attributes independently and contributes to the final priority score, making the overall complex system manageable through modular functional decomposition.
Data Source
AI summary
A method and apparatus assigns a quantative variable to each object (or set of objects) in a collection available to a user. The quantative variable is referred to as the Interest Priority Value (IPV). The IPV defines a range of states of the object, between ‘accessed’ and ‘unaccessed’, and is calculated based on one or more attributes of the object. A object with the highest IPV is the most ‘unaccessed,’ and the object with the lowest IPV is the least ‘unaccessed.’ The IPV may be used in a visual representation of the collection of objects, thereby permitting a user to readily identify and obtain those objects of greatest interest to the particular user.