Messaging search and management apparatuses, methods and systems

• US 10,229,205 B1
• Filed: 04/09/2018
• Issued: 03/12/2019
• Est. Priority Date: 10/14/2016
• Status: Active Grant

• Current Assignee: Salesforce.com, Inc.
• Original Assignee: Slack Technologies, Inc. (Salesforce.com, Inc.)
• Inventors: Grant, Myles, Mourachov, Serguei, Bourassa-Denis, Renaud, Liszka, Jason, Gallagher, John, Tromba, Isabella, Weiss, Noah, Butterfield, Daniel Stewart, Henderson-Begg, Callum
• Primary Examiner(s): Rostami, Mohammad S
• Application Number:
  US15/949,034
• Time in Patent Office: 337 Days
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: H04L 2101/365 Application layer names, e.g. buddy names, unstructured names chosen by a user or home appliance name
• CPC Class Codes: H04L 51/226 Delivery according to priorities
• CPC Class Codes: H04L 51/42 Mailbox-related aspects, e.g. synchronisation of mailboxes

Abstract

The Messaging Search and Management Apparatuses, Methods and Systems (“MSM”) transforms message, ranking request inputs via MSM components into work graphs, ML structure input data, ML structure, ranking response outputs. A work graph generation request that includes group level access control data may be obtained. A set of metadata access control carrying messages, a set of users, a set of channels, and a set of topics with access control data corresponding to the group level access control data may be determined. A user priority score for each of the other users, a channel priority score for each of the channels, and a topic priority score for each of the topics, from the perspective of each user, may be calculated. A work graph data structure may be generated that includes, for each user, data regarding the calculated user priority scores, channel priority scores, and topic priority scores.

Claims

1. A work graph generating apparatus, comprising:

a memory;

a component collection in the memory, including;

a work graph generating component;

a processor disposed in communication with the memory, and configured to issue a plurality of processing instructions from the component collection stored in the memory,

wherein the processor issues instructions from the work graph generating component, stored in the memory, to;

obtain, via at least one processor, a work graph generation request, wherein the work graph generation request includes group level access control data;

determine, via at least one processor, a set of metadata access control carrying messages, wherein access control data associated with metadata access control carrying messages in the set of metadata access control carrying messages corresponds to the group level access control data;

determine, via at least one processor, a set of users, wherein access control data associated with users in the set of users corresponds to the group level access control data;

calculate, via at least one processor, from the perspective of each user in the set of users, a channel priority score for each of the channels in the set of channels, wherein a channel priority score from the perspective of a user for a channel is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with that channel that were channel-pertinent to that user,

calculate, via at least one processor, from the perspective of each channel in the set of channels, a channel similarity score for each of the other channels in the set of channels, wherein a channel similarity score from the perspective of a first channel for a second channel is calculated based on the number of common users, in the set of users, that the first channel and the second channel share;

wherein the generated work graph structure includes a set of channel objects corresponding to the set of channels, wherein a channel object for a channel includes data regarding the calculated channel similarity score associated with that channel;

determine, via at least one processor, a set of topics associated with the set of metadata access control carrying messages;

generate, via at least one processor, a work graph data structure that includes a set of user objects corresponding to the set of users, wherein a user object for a user includes data regarding the calculated user priority scores, and channel priority scores associated with that user, and wherein the work graph data structure is associated with group level access control data.

2. The apparatus of claim 1, wherein the group level access control data is associated with an organization group.

3. The apparatus of claim 1, wherein the group level access control data is associated with a team group.

4. The apparatus of claim 1, wherein the set of metadata access control carrying messages is filtered to exclude metadata access control carrying messages sent outside a specified time period.

5. The apparatus of claim 1, wherein the user-pertinent metadata access control carrying messages are any of:

metadata access control carrying messages from the second user read by the first user, metadata access control carrying messages from the first user to the second user, metadata access control carrying messages from the second user responded to by the first user.

6. The apparatus of claim 5, wherein a response to a metadata access control carrying message is any of:

a reaction to the metadata access control carrying message, clicking on a link in the metadata access control carrying message, replying to the metadata access control carrying message, downloading a file associated with the metadata access control carrying message, sharing the metadata access control carrying message to another channel, pinning the metadata access control carrying message, starring the metadata access control carrying message.

7. The apparatus of claim 1, wherein the channel-pertinent metadata access control carrying messages associated with a channel for a user are any of:

metadata access control carrying messages sent by that user in that channel, metadata access control carrying messages read by that user in that channel, metadata access control carrying messages in that channel responded to by that user.

8. The apparatus of claim 1, wherein the topic-pertinent metadata access control carrying messages associated with a topic for a user are any of:

metadata access control carrying messages sent by that user regarding that topic, metadata access control carrying messages read by that user regarding that topic, metadata access control carrying messages regarding that topic responded to by that user.

9. The apparatus of claim 1, further, comprising:

the processor issues instructions from the work graph generating component, stored in the memory, to;

calculate, via at least one processor, from the perspective of each topic in the set of topics, a topic similarity score for each of the other topics in the set of topics;

wherein the generated work graph structure includes a set of topic objects corresponding to the set of topics, wherein a topic object for a topic includes data regarding the calculated topic similarity scores associated with that topic.

10. The apparatus of claim 1, wherein user priority scores between two users in the set of users are asymmetric.

11. The apparatus of claim 1, wherein user priority scores between two users in the set of users are symmetric.

12. The apparatus of claim 1, further, comprising:

a machine learning structure generating component in the component collection, and

the processor issues instructions from the machine learning structure generating component, stored in the memory, to;

determine, via at least one processor, a ranking application for which to generate a machine learning structure;

determine, via at least one processor, a set of inputs for the machine learning structure based on the ranking application, wherein at least some of the inputs in the set of inputs correspond to work graph data stored in the work graph data structure;

train, via at least one processor, the machine learning structure using at least some of the work graph data stored in the work graph data structure; and

store, via at least one processor, machine learning structure parameters of the trained machine learning structure, wherein the trained machine learning structure is associated with group level access control data.

13. The apparatus of claim 12, wherein the machine learning structure is a neural network.

14. The apparatus of claim 12, wherein the ranking application is any of:

ranking metadata access control carrying messages, ranking people, ranking channels.

15. A processor-readable work graph generating non-transient physical medium storing processor-executable components, the components, comprising:

a component collection stored in the medium, including;

a work graph generating component;

wherein the work graph generating component, stored in the medium, includes processor-issuable instructions to;

obtain, via at least one processor, a work graph generation request, wherein the work graph generation request includes group level access control data;

determine, via at least one processor, a set of metadata access control carrying messages, wherein access control data associated with metadata access control carrying messages in the set of metadata access control carrying messages corresponds to the group level access control data;

determine, via at least one processor, a set of users, wherein access control data associated with users in the set of users corresponds to the group level access control data;

calculate, via at least one processor, from the perspective of each user in the set of users, a user priority score for each of the other users in the set of users, wherein a user priority score from the perspective of a first user for a second user is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with the second user that were user-pertinent to the first user,

determine, via at least one processor, a set of channels, wherein access control data associated with channels in the set of channels corresponds to the group level access control data;

calculate, via at least one processor, from the perspective of each user in the set of users, a channel priority score for each of the channels in the set of channels, wherein a channel priority score from the perspective of a user for a channel is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with that channel that were channel-pertinent to that user,

calculate, via at least one processor, from the perspective of each channel in the set of channels, a channel similarity score for each of the other channels in the set of channels, wherein a channel similarity score from the perspective of a first channel for a second channel is calculated based on the number of common users, in the set of users, that the first channel and the second channel share;

wherein the generated work graph structure includes a set of channel objects corresponding to the set of channels, wherein a channel object for a channel includes data regarding the calculated channel similarity score associated with that channel;

determine, via at least one processor, a set of topics associated with the set of metadata access control carrying messages;

generate, via at least one processor, a work graph data structure that includes a set of user objects corresponding to the set of users, wherein a user object for a user includes data regarding the calculated user priority scores, and channel priority scores associated with that user, and wherein the work graph data structure is associated with group level access control data.

16. A processor-implemented work graph generating system, comprising:

a work graph generating component means, to;

obtain, via at least one processor, a work graph generation request, wherein the work graph generation request includes group level access control data;

determine, via at least one processor, a set of metadata access control carrying messages, wherein access control data associated with metadata access control carrying messages in the set of metadata access control carrying messages corresponds to the group level access control data;

determine, via at least one processor, a set of users, wherein access control data associated with users in the set of users corresponds to the group level access control data;

calculate, via at least one processor, from the perspective of each user in the set of users, a user priority score for each of the other users in the set of users, wherein a user priority score from the perspective of a first user for a second user is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with the second user that were user-pertinent to the first user,

determine, via at least one processor, a set of channels, wherein access control data associated with channels in the set of channels corresponds to the group level access control data;

calculate, via at least one processor, from the perspective of each user in the set of users, a channel priority score for each of the channels in the set of channels, wherein a channel priority score from the perspective of a user for a channel is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with that channel that were channel-pertinent to that user,

calculate, via at least one processor, from the perspective of each channel in the set of channels, a channel similarity score for each of the other channels in the set of channels, wherein a channel similarity score from the perspective of a first channel for a second channel is calculated based on the number of common users, in the set of users, that the first channel and the second channel share;

wherein the generated work graph structure includes a set of channel objects corresponding to the set of channels, wherein a channel object for a channel includes data regarding the calculated channel similarity score associated with that channel;

determine, via at least one processor, a set of topics associated with the set of metadata access control carrying messages;

generate, via at least one processor, a work graph data structure that includes a set of user objects corresponding to the set of users, wherein a user object for a user includes data regarding the calculated user priority scores, and channel priority scores associated with that user, and wherein the work graph data structure is associated with group level access control data.

17. A processor-implemented work graph generating method, comprising:

executing processor-implemented work graph generating component instructions to;

obtain, via at least one processor, a work graph generation request, wherein the work graph generation request includes group level access control data;

determine, via at least one processor, a set of metadata access control carrying messages, wherein access control data associated with metadata access control carrying messages in the set of metadata access control carrying messages corresponds to the group level access control data;

determine, via at least one processor, a set of users, wherein access control data associated with users in the set of users corresponds to the group level access control data;

calculate, via at least one processor, from the perspective of each user in the set of users, a user priority score for each of the other users in the set of users, wherein a user priority score from the perspective of a first user for a second user is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with the second user that were user-pertinent to the first user,

determine, via at least one processor, a set of channels, wherein access control data associated with channels in the set of channels corresponds to the group level access control data;

calculate, via at least one processor, from the perspective of each user in the set of users, a channel priority score for each of the channels in the set of channels, wherein a channel priority score from the perspective of a user for a channel is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with that channel that were channel-pertinent to that user,

calculate, via at least one processor, from the perspective of each channel in the set of channels, a channel similarity score for each of the other channels in the set of channels, wherein a channel similarity score from the perspective of a first channel for a second channel is calculated based on the number of common users, in the set of users, that the first channel and the second channel share;

wherein the generated work graph structure includes a set of channel objects corresponding to the set of channels, wherein a channel object for a channel includes data regarding the calculated channel similarity score associated with that channel;

determine, via at least one processor, a set of topics associated with the set of metadata access control carrying messages;

generate, via at least one processor, a work graph data structure that includes a set of user objects corresponding to the set of users, wherein a user object for a user includes data regarding the calculated user priority scores, and channel priority scores associated with that user, and wherein the work graph data structure is associated with group level access control data.