Matching service requester with service providers
Systems, methods, devices, and non-transitory, computer-readable storage media are disclosed for matching a service requester with a service provider via a taxonomy based directed graph. The method includes: receiving a keyword associated with a service; accessing a directed graph including a root node and nodes connected by edges, each node having a title; identifying a second node of the directed graph for each of service providers, each second node having a title matching a skill of a respective service provider; determining a distance between the first node and each second node along the directed graph; and ranking the service providers based at least in part on the distance between the first node and each second node. Systems, methods, devices, and non-transitory, computer-readable storage media are further disclosed for determining and storing a quality score for the revised linguistic content.
1. A method comprising:
receiving, by one or more processors, a linguistic document comprising a keyword associated with a translation service;
identifying, by the one or more processors, a first node of a directed graph, the directed graph including a root node and nodes connected by edges, each node having a title,
wherein the directed graph includes semantic paths, each semantic path being from the root node to a node having a title that at least partially matches the keyword, and
wherein the first node has a title matching the keyword associated with the translation service;
identifying, by the one or more processors, a second node of the directed graph for each of a plurality of service providers, each second node having a title matching a skill of a respective service provider,
wherein each second node is connected to a third node of the directed graph, the third node having a title indicating an identification (ID) of the respective service provider, and wherein the third node is connected to the second node corresponding to the respective service provider by an edge having a title indicating a language pair for the translation service;
determining, by the one or more processors, a distance between the first node and each second node along a particular semantic path in the directed graph, wherein the distance indicates a number of nodes connected by edges between the first node and each second node along the particular semantic path;
ranking, by the one or more processors, the plurality of service providers based at least in part on the distance between the first node and each second node;
performing, by the one or more processors, a machine translation of the linguistic document using a machine translation engine to generate a translated linguistic document; and
providing, by the one or more processors, the translated linguistic document to a particular service provider for enhancement, the particular service provider having been selected based on the ranking.
2. The method of claim 1 , comprising generating the directed graph.
3. The method of claim 2 , wherein generating the directed graph comprises:
in a main directed graph that includes a main root node and main nodes connected by main edges, identifying one or more of the main nodes that each has a title that at least partially matches the keyword;
determining a distance along the main directed graph from the main root node to each of the identified main nodes;
selecting one or more of the identified main nodes based on the distance from the main root node to each identified main node; and
generating the directed graph, wherein the selected main nodes are a plurality of nodes of the directed graph, each of the plurality of nodes having a title that at least partially matches the keyword.
4. The method of claim 3 , comprising selecting a predefined number of the identified main nodes.
5. The method of claim 3 , comprising generating the main directed graph based on a hierarchical classification of skills.
6. The method of claim 3 , comprising updating the main directed graph based on an update to a hierarchical classification of skills.
7. The method of claim 3 , comprising:
identifying the one or more of the main nodes using regular expressions.
8. The method of claim 1 , comprising ranking the plurality of service providers based at least in part on an indication of a capability of each service provider to provide the translation service from a first language to a second language.
9. The method of claim 1 , comprising ranking the plurality of service providers based in part on a quality metric for each service provider.
10. The method of claim 9 , comprising determining the quality metric for each service provider, wherein the quality metric for each service provider is based on a record for the service provider that is stored in a blockchain.
11. The method of claim 1 , further comprising anonymizing or redacting the linguistic document prior to performing the machine translation using the machine translation engine.
12. The method of claim 1 , wherein at least some of the plurality of service providers are linguistic content enhancers.
13. A system, comprising:
at least one processor; and
a memory storing instructions thereon that, when executed by the at least one processor, cause the at least one processor to perform the method of claim 1 .
14. A non-transitory, computer-readable storage medium having instructions stored thereon, that when executed by at least one processor, cause the at least one processor to perform the method of claim 1 .