Document Contributor Identification via Activity Scoring
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Solution Overview
Problem
In real-time online collaborative tools, it is difficult to identify key contributors to a document, leading to unnecessary communication and inaccurate answers, as existing systems lack actionable insights into user contributions.
Innovation Solution
A system analyzes user activities to generate contribution scores based on factors like editing time, data quantity, and type of edits, comparing these scores to a threshold to determine key contributors, which are then listed in the document's metadata for easy identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple users edit a document simultaneously in real-time collaborative tools, then document editing capability and collaboration are improved, but the ability to identify key contributors deteriorates
Solution Approach 1:
The patent segments the contribution of each user into specific factors (editing time, data quantity, edit type) and calculates separate contribution scores for each factor. This segmentation allows precise measurement of individual contributions even in multi-user collaborative environments, resolving the contradiction between improved collaboration and deteriorated contributor identification.
Solution Approach 2:
The patent transforms qualitative contribution information into quantitative parameters by defining contribution factors (editing time duration, data quantity metrics, edit type classifications) and calculating numerical contribution scores. This parameter transformation enables accurate identification of key contributors while maintaining real-time collaboration capabilities.
2Quantity of substance
If existing systems record user activity data, then data availability is improved, but actionable insights into user contributions deteriorate
Solution Approach 1:
The patent introduces contribution factors as intermediary elements that bridge raw user activity data and actionable insights. By defining specific contribution factors (editing time, data quantity, edit type) and calculating contribution scores based on these factors, the system transforms abundant raw data into meaningful, actionable information about user contributions.
Solution Approach 2:
The patent implements feedback by calculating contribution scores and comparing them against thresholds to identify key contributors. This feedback mechanism converts recorded user activity data into actionable insights that can guide document access decisions, communication routing, and collaboration management.
3Ease of operation
If readers communicate with multiple users to identify contributors, then communication channels are maintained, but time efficiency and accuracy deteriorate
Solution Approach 1:
The patent performs preliminary action by pre-calculating and storing contribution scores and key contributor identification in document metadata before readers need this information. This allows readers to immediately identify key contributors without initiating communication sequences, significantly reducing time loss while maintaining communication channels for when they are actually needed.
Solution Approach 2:
The patent enables self-service by providing automated key contributor identification through contribution score calculation and threshold comparison. The system serves itself by maintaining up-to-date contributor information in metadata, eliminating the need for readers to manually communicate with multiple users to identify appropriate contacts.
4Measurement precision
If contribution scores are calculated for all users, then identification accuracy is improved, but system processing complexity increases
Solution Approach 1:
The patent applies partial action by calculating contribution scores based on specific, predefined contribution factors (editing time, data quantity, edit type) rather than analyzing all possible user activities. This selective approach maintains high identification accuracy while reducing processing complexity by focusing only on the most relevant contribution dimensions.
Data Source
AI summary
A system for determining qualified contributors of a document is provided. A system can analyze user activities associated with a document to provide meaningful insights indicating the key contributors of the document based on a contributor policy. The contributor policy defines contribution factors and criteria that is used to determine when a user is deemed as a qualified contributor. The contribution factors can be used in an analysis of one or more user activities to determine a contribution score for each user associated with a document. The contribution scores of the users can be compared with a threshold to identify qualified contributors. The identified users are listed as qualified contributors of the document and associated with the document in the metadata. The contributor information can be utilized to inform readers of the document, identity expertise of these contributors, or recommend relevant documents to the contributors.