System and method for identification and consolidation of related concurrent document sessions
A cloud computing system identifies opportunities for users to collaborate on a file. Collaboration opportunities are identified based on similarity of separate files that different users are associated with, and on relationships or similarities between the different users. If users associated with the separate files agree to collaborate, the users may be placed in a single editing session regarding a file having content from at least one of the separate files.
1. A computer-implemented method of online document collaboration, comprising a processor at a server configured for:
identifying a first user associated with a first document editing session associated with a first file;
identifying a second user associated with a second document editing session associated with a second file;
storing a user similarity score between the first user and the second user in a user database;
storing a document similarity score between the first file and the second file in a resource database;
calculating a session similarity score between the first document editing session and the second document editing session, wherein the session similarity score is a combination of the user similarity score, the document similarity score, and historical data of users acceptance of suggestions to collaborate;
determining whether the session similarity score is greater than a threshold; and suggesting, in response to determining that the session similarity score is greater than the threshold, adding the second user as a collaborator to the first document editing session.
2. The method of claim 1 , wherein calculating the session similarity score further includes calculating a weighted average of the user similarity score and the document similarity score, and wherein weights are based on a confidence measurement.
3. The method of claim 2 , wherein calculating the session similarity score further includes calculating the confidence measurement based on an amount of data used to calculate the user similarity score and the document similarity score.
4. The method of claim 1 , wherein calculating the document similarity score is based in part on words, phrases and topics identified using natural language processing on a first document in the first document editing session and on a second document in the second document editing session.
5. The method of claim 4 , wherein calculating the document similarity score is based in part on an image analysis of images in the first document editing session and the second document editing session.
6. The method of claim 5 , wherein calculating the document similarity score is based in part on characteristics of users that have previously accessed or edited the first document in the first document editing session and the second document in the second document editing session.
7. The method of claim 6 , further comprising:
identifying a first plurality of users associated with the first document;
identifying a second plurality of users associated with the second document; and
wherein the user similarity score is further based on a weighted average of pairwise user similarity scores between each of the first plurality of users and the second plurality of users.
8. The method of claim 7 , further comprising adjusting the weighted average based on an amount of time each user in the first plurality of users and the second plurality of users has spent editing the first document.
9. The method of claim 1 , wherein determining whether the session similarity score is greater than the threshold further comprises determining the threshold based on pairwise session similarity scores for ail editing sessions on a cloud computing system.
10. The method of claim 1 , further comprising revising a weight used to calculate the session similarity score in response to the second user not joining the first document editing session when suggested.
11. A system for online document collaboration, comprising:
a document hardware processor in communication with:
a resource database comprising a memory for storing a document similarity score between a first file and a second file;
a user database comprising a memory for storing a user similarity score between a first user and a second user;
wherein the document hardware processor is configured to:
identify the first user, wherein the first user is associated with a first document editing session associated with the first file;
identify the second user, wherein the second user is associated with a second document editing session associated with the second file;
calculate a session similarity score between the first document editing session and the second document editing session, wherein the session similarity score is a combination of the user similarity score, the document similarity score, and historical data of users acceptance of suggestions to collaborate;
determine whether the session similarity score is greater than a threshold; and
suggest, in response to determining that the session similarity is greater than the threshold, adding the second user as a collaborator to the first document editing session.
12. The system of claim 11 , wherein the session similarity score is a weighted average of the user similarity score and the document similarity score, and wherein weights are based on a confidence measurement.
13. The system of claim 12 , wherein the confidence measurement is based on an amount of data used to calculate the user similarity score and the document similarity score.
14. The system of claim 11 , wherein the document similarity score is based in part on words, phrases and topics identified using natural language processing on a first document in the first document editing session and on a second document in the second document editing session.
15. The system of claim 14 , wherein the document similarity score is based in part on an image analysis of images in the first document editing session and the second document editing session.
16. The system of claim 15 , wherein the document similarity score is based in part on characteristics of users that have previously accessed or edited the first document in the first document editing session and the second document in the second document editing session.
17. The system of claim 16 , wherein the document hardware processor is further configured to:
identify a first plurality of users associated with the first document;
identify a second plurality of users associated with the second document; and
wherein the user similarity score is further based on a weighted average of pairwise user similarity scores between each of the first plurality of users and the second plurality of users.
18. The system of claim 17 , wherein the weighted average is adjusted based on an amount of time each user in the first plurality of users and the second plurality of users has spent editing the first document.
19. The system of claim 11 , wherein the threshold is determined based on pairwise session similarity scores for all editing sessions on a cloud computing system.
20. The system of claim 11 , wherein a weight used to calculate the session similarity score is revised in response to the second user not joining the first document editing session when suggested.