Automated Collaboration Suggestion for Document Similarity
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing productivity applications face challenges in sharing and collaborating on locally generated documents, as these processes can be slow and prone to errors.
Innovation Solution
The implementation of automated collaboration within networked productivity applications, which involves identifying collaborative similarities between documents based on content and additional information, and generating collaboration suggestions for users to work together on shared content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If locally generated documents are shared manually, then document sharing is possible, but the process is slow and prone to error
Solution Approach 1:
The system performs preliminary actions by automatically analyzing document content, metadata, and user profiles before collaboration is requested. It pre-identifies potential collaborators and prepares collaboration suggestions, eliminating the need for manual document sharing and reducing both time and errors in the collaboration setup process
Solution Approach 2:
The system enables self-service by automatically matching documents with potential collaborators based on content similarity and user preferences. The automated collaboration suggestion system eliminates manual intervention in the document sharing process, reducing human error while maintaining fast collaboration initiation
2Productivity
If automated collaboration suggestions are generated, then collaboration efficiency is improved, but system complexity increases
Solution Approach 1:
The server implements multi-functionality by combining document analysis, similarity computation, user profile matching, and collaboration suggestion generation in a single automated system. This universal approach handles multiple collaboration tasks simultaneously, improving efficiency without proportionally increasing complexity
Solution Approach 2:
The system incorporates feedback mechanisms where collaboration suggestions are generated based on analyzed data, user responses to suggestions are collected, and the system learns from this feedback to improve future matching accuracy. This feedback loop enhances productivity while managing complexity through iterative improvement rather than complex upfront design
Data Source
AI summary
A method for suggesting collaboration between a plurality of users of a communication system includes identifying a first document pertaining to a first event associated with a first user, determining that collaboration is allowed for the first document, identifying a second document having a collaborative similarity with the first document and pertaining to a second event and associated with a second user, generating a collaboration suggestion for collaboration between the first user and the second user with respect to the first event, providing the collaboration suggestion to collaborate with respect to the first event on a user device of the first user, receiving an indication of an acceptance, by the first user, of the collaboration suggestion, and causing a collaboration session to be established between the user device of the first user and a user device of the second user to collaborate with respect to the first event.