Expandable data object management and indexing architecture for intersystem data exchange compatibility
A group-based communication platform is configured to ascertain the relatedness of various work objects shared among users of the group-based communication platform. Moreover, the group-based communication platform may further receive and process work objects originating from non-users of the group-based communication platform, thereby further expanding the utility of the determined relatedness between work objects. These work objects (or encrypted representations of these work objects) may be indexed and stored in association with the group-based communication platform, thereby enabling users to search for and retrieve work objects originating from a plurality of work object sources simultaneously, and based on various characteristics of those work objects and the determined interrelatedness between various work objects.
1. A group-based communication platform configured for indexing personal work objects within a database storage area, the group-based communication platform comprising:
one or more memory storage areas; and
one or more processors collectively configured to:
intake one or more personal work objects from a client device associated with a specific user identifier, wherein the one or more personal work objects comprise content data and metadata designating each of the one or more personal work objects as personal to the specific user identifier;
extract work object data from each of the one or more personal work objects;
define links for each of the one or more personal work objects within an existing work graph data structure interrelating the one or more personal work objects with other work objects represented within the existing work graph data structure; and
index the one or more personal work objects for retrieval by the client device associated with the specific user identifier based at least in part on characteristics of the one or more personal work objects identified by the defined links.
2. The group-based communication platform of claim 1 , wherein the one or more processors are further configured to represent the one or more personal work objects as encrypted work objects within the existing work graph data structure.
3. The group-based communication platform of claim 1 , wherein the characteristics of the one or more personal work objects are determined based at least in part on a term-frequency, inverse-document frequency analysis to identify relevant terms to be assigned as topics for each of the one or more personal work objects.
4. The group-based communication platform of claim 1 , wherein the one or more personal work objects comprise tasks.
5. The group-based communication platform of claim 1 , wherein the links are defined between work objects of differing work object types.
6. The group-based communication platform of claim 1 , wherein the one or more processors are further configured to execute a query function based at least in part on a query request received from the client device associated with the specific user identifier, wherein the query function comprises:
querying work objects based at least in part on the query request;
ranking one or more work objects based on relevance to the query request and based on relatedness between work objects as established within the existing work graph data structure, wherein the one or more ranked work objects comprise at least one of the one or more personal work objects; and
transmitting cache objects to the client device indicative of the one or more ranked work objects identified from the querying.
7. The group-based communication platform of claim 1 , wherein the one or more processors are further configured to generate a neural network for executing a search query based at least in part on the existing work graph data structure.
8. A computer-implemented method for indexing personal work objects within a database storage area, the method comprising:
intaking one or more personal work objects from a client device associated with a specific user identifier, wherein the one or more personal work objects comprise content data and metadata designating each of the one or more personal work objects as personal to the specific user identifier;
extracting work object data from each of the one or more personal work objects;
defining links for each of the one or more personal work objects within an existing work graph data structure interrelating the one or more personal work objects with other work objects represented within the existing work graph data structure; and
indexing the one or more personal work objects for retrieval by the client device associated with the specific user identifier based at least in part on characteristics of the one or more personal work objects identified by the defined links.
9. The computer-implemented method of claim 8 , further comprising representing the one or more personal work objects as encrypted work objects within the existing work graph data structure.
10. The computer-implemented method of claim 8 , wherein the characteristics of the one or more personal work objects are determined based at least in part on a term-frequency, inverse-document frequency analysis to identify relevant terms to be assigned as topics for each of the one or more personal work objects.
11. The computer-implemented method of claim 8 , wherein the one or more personal work objects comprise tasks.
12. The computer-implemented method of claim 8 , wherein the links are defined between work objects of differing work object types.
13. The computer-implemented method of claim 8 , further comprising executing a query function based at least in part on a query request received from the client device associated with the specific user identifier, wherein the query function comprises:
querying work objects based at least in part on the query request;
ranking one or more work objects based on relevance to the query request and based on relatedness between work objects as established within the existing work graph data structure, wherein the one or more ranked work objects comprise at least one of the one or more personal work objects; and
transmitting cache objects to the client device indicative of the one or more ranked work objects identified from the querying.
14. The computer-implemented method of claim 8 , further comprising generating a neural network for executing a search query based at least in part on the existing work graph data structure.
15. A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising an executable portion configured to cause a computer processor to:
intake one or more personal work objects from a client device associated with a specific user identifier, wherein the one or more personal work objects comprise content data and metadata designating each of the one or more personal work objects as personal to the specific user identifier;
extract work object data from each of the one or more personal work objects;
define links for each of the one or more personal work objects within an existing work graph data structure interrelating the one or more personal work objects with other work objects represented within the existing work graph data structure; and
index the one or more personal work objects for retrieval by the client device associated with the specific user identifier based at least in part on characteristics of the one or more personal work objects identified by the defined links.
16. The computer program product of claim 15 , wherein the executable portion is further configured to cause the processor to represent the one or more personal work objects as encrypted work objects within the existing work graph data structure.
17. The computer program product of claim 15 , wherein the characteristics of the one or more personal work objects are determined based at least in part on a term-frequency, inverse-document frequency analysis to identify relevant terms to be assigned as topics for each of the one or more personal work objects.
18. The computer program product of claim 15 , wherein the one or more personal work objects comprise tasks.
19. The computer program product of claim 15 , wherein the links are defined between work objects of differing work object types.
20. The computer program product of claim 15 , wherein the executable portion is further configured to cause the processor to execute a query function based at least in part on a query request received from the client device associated with the specific user identifier, wherein the query function comprises:
querying work objects based at least in part on the query request;
ranking one or more work objects based on relevance to the query request and based on relatedness between work objects as established within the existing work graph data structure, wherein the one or more ranked work objects comprise at least one of the one or more personal work objects; and
transmitting cache objects to the client device indicative of the one or more ranked work objects identified from the querying.
21. The computer program product of claim 15 , wherein the executable portion is further configured to cause the processor to generate a neural network for executing a search query based at least in part on the existing work graph data structure.