Score Documents to a Job🔗︎
HTTP Verb | Path |
---|---|
POST | /v10/scorer/bimetric/joborder |
Score a group of resumes/jobs (that aren't indexed) to a parsed job. It's highly recommended to index all of your documents and leverage the speed and power of the Search & Match Engine and use one of the Search & Match endpoints. This will also reduce your overall cost as the bimetric scoring is a higher charge per transaction.
Info
- You can try this endpoint out at our Swagger page ( US Data Center | EU Data Center | AU Data Center )
Request Body🔗︎
SourceJob 🔗︎ object
required
SourceJob🔗︎
Parsed job to match against each of the target documents.
SourceJob properties
Id 🔗︎ string
required
Id🔗︎
Id of the source document. This isn't used in any calculation, only to assist in displaying output.
JobData 🔗︎ string
required
JobData🔗︎
The parsed JobData
from the Textkernel Job Parser. See Parse a Job
TargetJobs 🔗︎ object[]
TargetJobs🔗︎
Array of parsed jobs to be matched against the source resume.
TargetJobs properties
Id 🔗︎ string
required
Id🔗︎
Id of the target job. This isn't used in any calculation, only to assist in displaying output.
JobData 🔗︎ object
required
JobData🔗︎
The parsed JobData
from the Textkernel Job Parser. See Parse a Job
TargetResumes 🔗︎ object[]
TargetResumes🔗︎
Array of parsed resumes to be matched against the source resume.
TargetResumes properties
Id 🔗︎ string
required
Id🔗︎
Id of the target job. This isn't used in any calculation, only to assist in displaying output.
ResumeData 🔗︎ object
required
ResumeData🔗︎
Parsed ResumeData
from the Textkernel CV/Resume Parser. See Parse a Resume
PreferredCategoryWeights 🔗︎ object
PreferredCategoryWeights🔗︎
The weights you want to use for scoring.It is important to specify these, otherwise default values will be used.
These weights will be used except in the case that you provided a non-zero weight for a category that is irrelevant in the source document. For example, this can happen when the source document contains no languages.
PreferredCategoryWeights properties
JobTitles 🔗︎ decimal
JobTitles🔗︎
The weight of the JobTitles category relative to other categories..
Industries 🔗︎ decimal
Industries🔗︎
The weight of the Industries/Taxonomies category relative to other categories.
Certifications 🔗︎ decimal
Certifications🔗︎
The weight of the Certifications category relative to other categories.
Sample JSON
{
"SourceJob": {
"Id": "",
"JobData": "..."
},
"TargetResumes": [
{
"Id": "",
"ResumeData": "..."
}
],
"TargetJobs": [
{
"Id": "",
"JobData": "..."
}
],
"Settings": {
"PositionTitlesMustHaveAnExactMatch": false
},
"PreferredCategoryWeights": {
"Education": 0,
"JobTitles": 0,
"Skills": 0,
"Industries": 0,
"Languages": 0,
"Certifications": 0,
"ExecutiveType": 0,
"ManagementLevel": 0
}
}
Response Body🔗︎
Info 🔗︎ object
Info🔗︎
Information explaining the outcome of the transaction.
Info properties
Code 🔗︎ object[]
Code🔗︎
Code | Description |
---|---|
Success |
Successful transaction |
MissingParameter |
A required parameter wasn't provided |
InvalidParameter |
A parameter was incorrectly specified |
AuthenticationError |
An error occurred with the credentials provided |
TransactionId 🔗︎ string
TransactionId🔗︎
The (GUID) id for a specific API transaction. Use this when contacting support@textkernel.com about issues.
EngineVersion 🔗︎ string
EngineVersion🔗︎
The version of the parsing/matching engine running under-the-hood.
TotalElapsedMilliseconds 🔗︎ integer
TotalElapsedMilliseconds🔗︎
How long the transaction took on Textkernel's server, in milliseconds. If the transaction takes longer to complete on the client side, that extra duration is solely network latency.
TransactionCost 🔗︎ decimal
TransactionCost🔗︎
How many credits the transaction costs.How many credits the transaction costs.
CustomerDetails 🔗︎ object
CustomerDetails🔗︎
Information about the customer who made the API call.
CustomerDetails properties
CreditsRemaining 🔗︎ decimal
CreditsRemaining🔗︎
The number of credits remaining to be used by the account.
Value 🔗︎ object
Value🔗︎
Contains response data for the transaction.
Value properties
Matches 🔗︎ object[]
Matches🔗︎
An object[] containing the results for each match result.
Matches properties
SovScore 🔗︎ integer
SovScore🔗︎
An integer score from 0-100 representing the overall fit of the match. Results are sorted by this parameter in descending order.
EnrichedScoreData 🔗︎ object
EnrichedScoreData🔗︎
Detailed information about the source to target match.
EnrichedScoreData properties
Languages 🔗︎ object
Languages🔗︎
Detailed match information for the Languages category.
Languages properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Certifications 🔗︎ object
Certifications🔗︎
Detailed match information for the Certifications category.
Certifications properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
ExecutiveType 🔗︎ object
ExecutiveType🔗︎
Detailed match information for the ExecutiveType category.
ExecutiveType properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Education 🔗︎ object
Education🔗︎
Detailed match information for the Eduction category.
Education properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Taxonomies 🔗︎ object
Taxonomies🔗︎
Detailed match information for the Taxonomies category.
Taxonomies properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
ActualTaxonomies 🔗︎ object
ActualTaxonomies🔗︎
Taxonomies found.
ActualTaxonomies properties
Primary 🔗︎ object
Primary🔗︎
Best fit taxonomy evidence.
Primary properties
DesiredTaxonomies 🔗︎ object
DesiredTaxonomies🔗︎
Taxonomies requested.
DesiredTaxonomies properties
Primary 🔗︎ object
Primary🔗︎
Best fit taxonomy evidence.
Primary properties
JobTitles 🔗︎ object
JobTitles🔗︎
Detailed match information for the JobTitles category.
JobTitles properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
Skills 🔗︎ object
Skills🔗︎
Detailed match information for the Skills category.
Skills properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
ManagementLevel 🔗︎ object
ManagementLevel🔗︎
Detailed match information for the ManagementLevel category.
ManagementLevel properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
EnrichedRCSScoreData 🔗︎ object
EnrichedRCSScoreData🔗︎
Detailed information about the target to source match.
EnrichedRCSScoreData properties
Languages 🔗︎ object
Languages🔗︎
Detailed match information for the Languages category.
Languages properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Certifications 🔗︎ object
Certifications🔗︎
Detailed match information for the Certifications category.
Certifications properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
ExecutiveType 🔗︎ object
ExecutiveType🔗︎
Detailed match information for the ExecutiveType category.
ExecutiveType properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Education 🔗︎ object
Education🔗︎
Detailed match information for the Eduction category.
Education properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Taxonomies 🔗︎ object
Taxonomies🔗︎
Detailed match information for the Taxonomies category.
Taxonomies properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
ActualTaxonomies 🔗︎ object
ActualTaxonomies🔗︎
Taxonomies found.
ActualTaxonomies properties
Primary 🔗︎ object
Primary🔗︎
Best fit taxonomy evidence.
Primary properties
DesiredTaxonomies 🔗︎ object
DesiredTaxonomies🔗︎
Taxonomies requested.
DesiredTaxonomies properties
Primary 🔗︎ object
Primary🔗︎
Best fit taxonomy evidence.
Primary properties
JobTitles 🔗︎ object
JobTitles🔗︎
Detailed match information for the JobTitles category.
JobTitles properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
Skills 🔗︎ object
Skills🔗︎
Detailed match information for the Skills category.
Skills properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
ManagementLevel 🔗︎ object
ManagementLevel🔗︎
Detailed match information for the ManagementLevel category.
ManagementLevel properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
WeightedScore 🔗︎ integer
WeightedScore🔗︎
An integer score from 0-100 representing how well the source document matched the current document. This calculation is the sum of the unweighted category scores multiplied by their respective suggested weight.
UnweightedCategoryScores 🔗︎ object[]
Deprecated
UnweightedCategoryScores🔗︎
Deprecated
UnweightedCategoryScores properties
ReverseCompatibilityScore 🔗︎ integer
ReverseCompatibilityScore🔗︎
An integer score from 0-100 which represents how well the target document matched to the source document. This isn't the same as WeightedScore because when doing the reverse calculation we are analyzing for all of the data from the target document to be found in the source document.
SuggestedCategoryWeights 🔗︎ object
SuggestedCategoryWeights🔗︎
The weights suggested by Textkernel based solely on the data in the source document.
NOTE: these should only be used as a fallback or initial value. Your system/users should have the ability to adjust/override these (in the PreferredCategoryWeights
in the request)
SuggestedCategoryWeights properties
JobTitles 🔗︎ decimal
JobTitles🔗︎
The weight of the JobTitles category relative to other categories..
Industries 🔗︎ decimal
Industries🔗︎
The weight of the Industries/Taxonomies category relative to other categories.
Certifications 🔗︎ decimal
Certifications🔗︎
The weight of the Certifications category relative to other categories.
ExecutiveType 🔗︎ decimal
ExecutiveType🔗︎
The weight of the ExecutiveType category relative to other categories.
ManagementLevel 🔗︎ decimal
ManagementLevel🔗︎
The weight of the ManagementLevel category relative to other categories.
EducationHasData 🔗︎ boolean
EducationHasData🔗︎
If false, the Education category has no data and should be ignored/hidden.
JobTitlesHasData 🔗︎ boolean
JobTitlesHasData🔗︎
If false, the JobTitles category has no data and should be ignored/hidden.
SkillsHasData 🔗︎ boolean
SkillsHasData🔗︎
If false, the Skills category has no data and should be ignored/hidden.
IndustriesHasData 🔗︎ boolean
IndustriesHasData🔗︎
If false, the Industries/Taxonomies category has no data and should be ignored/hidden.
LanguagesHasData 🔗︎ boolean
LanguagesHasData🔗︎
If false, the Languages category has no data and should be ignored/hidden.
CertificationsHasData 🔗︎ boolean
CertificationsHasData🔗︎
If false, the Certifications category has no data and should be ignored/hidden.
AppliedCategoryWeights 🔗︎ object
AppliedCategoryWeights🔗︎
The weights that were actually used for scoring. These are either
1) if the PreferredCategoryWeights
are specified in the request, these are used (with any adjustments for non-applicable categories)
2) otherwise these are simply the SuggestedCategoryWeights
AppliedCategoryWeights properties
JobTitles 🔗︎ decimal
JobTitles🔗︎
The weight of the JobTitles category relative to other categories..
Industries 🔗︎ decimal
Industries🔗︎
The weight of the Industries/Taxonomies category relative to other categories.
Certifications 🔗︎ decimal
Certifications🔗︎
The weight of the Certifications category relative to other categories.
Sample JSON
{
"Info": {
"Code": "string",
"Message": "string",
"TransactionId": "string",
"EngineVersion": "string",
"ApiVersion": "string",
"TotalElapsedMilliseconds": 0,
"TransactionCost": 0,
"CustomerDetails": {
"AccountId": "string",
"Name": "string",
"IPAddress": "string",
"Region": "string",
"CreditsRemaining": 0,
"CreditsUsed": 0,
"ExpirationDate": "2021-12-31",
"MaximumConcurrentRequests": 0
}
},
"Value": {
"Matches": [
{
"Id": "",
"SovScore": 0,
"EnrichedScoreData": {
"Languages": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Certifications": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"ExecutiveType": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Education": {
"UnweightedScore": 0,
"ExpectedEducation": "",
"ActualEducation": "",
"Comparison": "",
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Taxonomies": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"ActualTaxonomies": {
"Primary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
},
"Secondary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
}
},
"DesiredTaxonomies": {
"Primary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
},
"Secondary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
}
}
},
"JobTitles": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"Found": [
{
"RawTerm": "",
"VariationOf": "",
"IsCurrent": false
}
],
"NotFound": [
""
]
},
"Skills": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"Found": [
{
"Skill": "",
"IsCurrent": false
}
],
"NotFound": [
""
]
},
"ManagementLevel": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"Actual": "",
"Desired": "",
"AmountOfExperienceMatches": false
}
},
"EnrichedRCSScoreData": {
"Languages": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Certifications": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"ExecutiveType": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Education": {
"UnweightedScore": 0,
"ExpectedEducation": "",
"ActualEducation": "",
"Comparison": "",
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Taxonomies": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"ActualTaxonomies": {
"Primary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
},
"Secondary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
}
},
"DesiredTaxonomies": {
"Primary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
},
"Secondary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
}
}
},
"JobTitles": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"Found": [
{
"RawTerm": "",
"VariationOf": "",
"IsCurrent": false
}
],
"NotFound": [
""
]
},
"Skills": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"Found": [
{
"Skill": "",
"IsCurrent": false
}
],
"NotFound": [
""
]
},
"ManagementLevel": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"Actual": "",
"Desired": "",
"AmountOfExperienceMatches": false
}
},
"WeightedScore": 0,
"UnweightedCategoryScores": [
{
"Category": "",
"UnweightedScore": 0,
"TermsFound": [
""
]
}
],
"ReverseCompatibilityScore": 0
}
],
"SuggestedCategoryWeights": {
"Education": 0,
"JobTitles": 0,
"Skills": 0,
"Industries": 0,
"Languages": 0,
"Certifications": 0,
"ExecutiveType": 0,
"ManagementLevel": 0,
"EducationHasData": false,
"JobTitlesHasData": false,
"SkillsHasData": false,
"IndustriesHasData": false,
"LanguagesHasData": false,
"CertificationsHasData": false,
"ExecutiveTypeHasData": false,
"ManagementLevelHasData": false
},
"AppliedCategoryWeights": {
"Education": 0,
"JobTitles": 0,
"Skills": 0,
"Industries": 0,
"Languages": 0,
"Certifications": 0,
"ExecutiveType": 0,
"ManagementLevel": 0
}
}
}