Cloudmersive

Cloudmersive Analytics API

Analytics operations of the Cloudmersive Natural Language Processing (NLP) API v2 — 5 operation(s) served from https://api.cloudmersive.com and authenticated with the Apikey header. One Cloudmersive API key grants access to every API in the portfolio.

GitHub OpenAPI

Operations 5

POST /nlp-v2/analytics/sentiment Perform Sentiment Analysis and Classification on Text #
POST /nlp-v2/analytics/profanity Perform Profanity and Obscene Language Analysis and Detection on Text #
POST /nlp-v2/analytics/hate-speech Perform Hate Speech Analysis and Detection on Text #
POST /nlp-v2/analytics/subjectivity Perform Subjectivity and Objectivity Analysis on Text #
POST /nlp-v2/analytics/similarity Perform Semantic Similarity Comparison of Two Strings #

Documentation

📖
Documentation
https://api.cloudmersive.com/docs/nlp.asp
📖
APIReference
https://api-console.cloudmersive.com/swagger/index.html?urls.primaryName=Natural%20Language%20Processing%20(NLP)%20API%20v2

Specifications

⚙
OpenAPI
https://artifacts.apis.io/cloudmersive/openapi/cloudmersive-analytics-api-openapi.yml
⚙
OpenAPI
https://api-console.cloudmersive.com/swagger/api/spec/nlpv2

Schemas & Data

📊
JSONSchema
https://artifacts.apis.io/cloudmersive/json-schema/cloudmersive-sentiment-analysis-response-schema.json
📊
JSONSchema
https://artifacts.apis.io/cloudmersive/json-schema/cloudmersive-profanity-analysis-response-schema.json
📊
JSONSchema
https://artifacts.apis.io/cloudmersive/json-schema/cloudmersive-hate-speech-analysis-response-schema.json
📊
JSONSchema
https://artifacts.apis.io/cloudmersive/json-schema/cloudmersive-subjectivity-analysis-response-schema.json
📊
JSONSchema
https://artifacts.apis.io/cloudmersive/json-schema/cloudmersive-similarity-analysis-response-schema.json
📊
JSONSchema
https://artifacts.apis.io/cloudmersive/json-schema/cloudmersive-similarity-analysis-request-schema.json

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OpenAPI Specification

cloudmersive-analytics-api-openapi.yml Raw ↑ 
openapi: 3.2.0
info:
  version: v1
  title: nlpapiv2 Analytics API
  description: The powerful Natural Language Processing APIs (v2) let you perform part of speech tagging, entity identification, sentence parsing, and much more to help you understand the meaning of unstructured text.
servers:
- url: https://testapi.cloudmersive.com
tags:
- name: Analytics
paths:
  /nlp-v2/analytics/sentiment:
    post:
      tags:
      - Analytics
      summary: Perform Sentiment Analysis and Classification on Text
      description: Analyze input text using advanced Sentiment Analysis to determine if the input is positive, negative, or neutral. Supports English language input. Consumes 1-2 API calls per sentence.
      operationId: Analytics_Sentiment
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/SentimentAnalysisResponse'
      security:
      - Apikey: []
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/SentimentAnalysisRequest'
          text/json:
            schema:
              $ref: '#/components/schemas/SentimentAnalysisRequest'
          application/xml:
            schema:
              $ref: '#/components/schemas/SentimentAnalysisRequest'
          text/xml:
            schema:
              $ref: '#/components/schemas/SentimentAnalysisRequest'
          application/x-www-form-urlencoded:
            schema:
              $ref: '#/components/schemas/SentimentAnalysisRequest'
        description: Input sentiment analysis request
        required: true
  /nlp-v2/analytics/profanity:
    post:
      tags:
      - Analytics
      summary: Perform Profanity and Obscene Language Analysis and Detection on Text
      description: Analyze input text using advanced Profanity and Obscene Language Analysis to determine if the input contains profane language. Supports English language input. Consumes 1-2 API calls per sentence.
      operationId: Analytics_Profanity
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProfanityAnalysisResponse'
      security:
      - Apikey: []
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/ProfanityAnalysisRequest'
          text/json:
            schema:
              $ref: '#/components/schemas/ProfanityAnalysisRequest'
          application/xml:
            schema:
              $ref: '#/components/schemas/ProfanityAnalysisRequest'
          text/xml:
            schema:
              $ref: '#/components/schemas/ProfanityAnalysisRequest'
          application/x-www-form-urlencoded:
            schema:
              $ref: '#/components/schemas/ProfanityAnalysisRequest'
        description: Input profanity analysis request
        required: true
  /nlp-v2/analytics/hate-speech:
    post:
      tags:
      - Analytics
      summary: Perform Hate Speech Analysis and Detection on Text
      description: Analyze input text using advanced Hate Speech Analysis to determine if the input contains hate speech language. Supports English language input. Consumes 1-2 API calls per sentence.
      operationId: Analytics_HateSpeech
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HateSpeechAnalysisResponse'
      security:
      - Apikey: []
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/HateSpeechAnalysisRequest'
          text/json:
            schema:
              $ref: '#/components/schemas/HateSpeechAnalysisRequest'
          application/xml:
            schema:
              $ref: '#/components/schemas/HateSpeechAnalysisRequest'
          text/xml:
            schema:
              $ref: '#/components/schemas/HateSpeechAnalysisRequest'
          application/x-www-form-urlencoded:
            schema:
              $ref: '#/components/schemas/HateSpeechAnalysisRequest'
        description: Input hate speech analysis request
        required: true
  /nlp-v2/analytics/subjectivity:
    post:
      tags:
      - Analytics
      summary: Perform Subjectivity and Objectivity Analysis on Text
      description: Analyze input text using advanced Subjectivity and Objectivity Language Analysis to determine if the input text is objective or subjective, and how much. Supports English language input. Consumes 1-2 API calls per sentence.
      operationId: Analytics_Subjectivity
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/SubjectivityAnalysisResponse'
      security:
      - Apikey: []
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/SubjectivityAnalysisRequest'
          text/json:
            schema:
              $ref: '#/components/schemas/SubjectivityAnalysisRequest'
          application/xml:
            schema:
              $ref: '#/components/schemas/SubjectivityAnalysisRequest'
          text/xml:
            schema:
              $ref: '#/components/schemas/SubjectivityAnalysisRequest'
          application/x-www-form-urlencoded:
            schema:
              $ref: '#/components/schemas/SubjectivityAnalysisRequest'
        description: Input subjectivity analysis request
        required: true
  /nlp-v2/analytics/similarity:
    post:
      tags:
      - Analytics
      summary: Perform Semantic Similarity Comparison of Two Strings
      description: Analyze two input text strings, typically sentences, and determine the semantic similarity of each. Semantic similarity refers to the degree to which two sentences mean the same thing semantically. Uses advanced Deep Learning to perform the semantic similarity comparison. Consumes 1-2 API calls per sentence.
      operationId: Analytics_Similarity
      responses:
        '200':
          description: OK
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/SimilarityAnalysisResponse'
      security:
      - Apikey: []
      requestBody:
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/SimilarityAnalysisRequest'
          text/json:
            schema:
              $ref: '#/components/schemas/SimilarityAnalysisRequest'
          application/xml:
            schema:
              $ref: '#/components/schemas/SimilarityAnalysisRequest'
          text/xml:
            schema:
              $ref: '#/components/schemas/SimilarityAnalysisRequest'
          application/x-www-form-urlencoded:
            schema:
              $ref: '#/components/schemas/SimilarityAnalysisRequest'
        description: Input similarity analysis request
        required: true
components:
  schemas:
    SubjectivityAnalysisRequest:
      description: Input to a subjectivity analysis operation
      type: object
      properties:
        TextToAnalyze:
          description: Text to analyze
          type: string
    SimilarityAnalysisResponse:
      description: Output of a similarity analysis operation
      type: object
      properties:
        Successful:
          description: True if the similarity analysis operation was successful, false otherwise
          type: boolean
        SimilarityScoreResult:
          format: double
          description: Similarity score between 0.0 and 1.0 where scores closer to zero have a low probability of semantic similarity, while scores close to 1.0 have a high probability of semantic similarity.
          type: number
        SentenceCount:
          format: int32
          description: Number of sentences in input text
          type: integer
    SubjectivityAnalysisResponse:
      description: Output of a subjectivity analysis operation
      type: object
      properties:
        Successful:
          description: True if the subjectivity analysis operation was successful, false otherwise
          type: boolean
        SubjectivityScoreResult:
          format: double
          description: Subjectivity vs. objectivity classification score between 0.0 and 1.0 where scores closer to zero have a high probability of objectivity, while scores close to 1.0 have a high probability of subjectivity.
          type: number
        SentenceCount:
          format: int32
          description: Number of sentences in input text
          type: integer
    SentimentAnalysisResponse:
      description: Output of a sentiment analysis operation
      type: object
      properties:
        Successful:
          description: True if the sentiment analysis operation was successful, false otherwise
          type: boolean
        SentimentClassificationResult:
          description: Classification of input text into a sentiment classification; possible values are "Positive", "Negative" or "Neutral"
          type: string
        SentimentScoreResult:
          format: double
          description: Sentiment classification score between -1.0 and +1.0 where scores less than 0 are negative sentiment, scores greater than 0 are positive sentiment and scores close to 0 are neutral.  The greater the value deviates from 0.0 the stronger the sentiment, with +1.0 and -1.0 being maximum positive and negative sentiment, respectively.
          type: number
        SentenceCount:
          format: int32
          description: Number of sentences in input text
          type: integer
    SentimentAnalysisRequest:
      description: Input to a sentiment analysis operation
      type: object
      properties:
        TextToAnalyze:
          description: Text to analyze
          type: string
    HateSpeechAnalysisResponse:
      description: Output of a hate speech analysis operation
      type: object
      properties:
        Successful:
          description: True if the profanity detection operation was successful, false otherwise
          type: boolean
        HateSpeechScoreResult:
          format: double
          description: Hate speech classification score between 0.0 and 1.0 where scores closer to zero have a low probability of being hate speech language, while scores close to 1.0 have a high probability of being hate speech language.  Values above 0.8 have a very high probability of being hate speech.
          type: number
        SentenceCount:
          format: int32
          description: Number of sentences in input text
          type: integer
    SimilarityAnalysisRequest:
      description: Input to a similarity analysis operation
      type: object
      properties:
        TextToAnalyze1:
          description: First text to analyze
          type: string
        TextToAnalyze2:
          description: Second text to analyze
          type: string
    ProfanityAnalysisRequest:
      description: Input to a profanity analysis operation
      type: object
      properties:
        TextToAnalyze:
          description: Text to analyze
          type: string
    HateSpeechAnalysisRequest:
      description: Input to a hate speech analysis operation
      type: object
      properties:
        TextToAnalyze:
          description: Text to analyze
          type: string
    ProfanityAnalysisResponse:
      description: Output of a profanity analysis operation
      type: object
      properties:
        Successful:
          description: True if the profanity detection operation was successful, false otherwise
          type: boolean
        ProfanityScoreResult:
          format: double
          description: Profanity classification score between 0.0 and 1.0 where scores closer to zero have a low probability of being profane or contain obscene language, while scores close to 1.0 have a high probability of being profane or containing obscene language.  Values above 0.8 have a very high probability of being profane.
          type: number
        SentenceCount:
          format: int32
          description: Number of sentences in input text
          type: integer
  securitySchemes:
    Apikey:
      type: apiKey
      description: API Key Authentication
      name: Apikey
      in: header
x-provenance:
  method: harvested
  publisher: Cloudmersive
  source: https://api-console.cloudmersive.com/swagger/api/spec/nlpv2
  note: split by refine-openapis from the provider's own published document, verified by fetch (openapi/_original/*.fetch.json);
    stamped by stamp-openapi-provenance.py (roadmap#793)