Topics

This API helps you detect topics, entities, concepts, keywords, and key-phrases from the input text

Overview

Extract the most relevant topics, concepts, discussion points from the text are generated based on the overall text chunk (Global Topics) or by each paragraph/sentence (Topics by Sentence).

Input Type Supported: Text

Types of Topics

Type

Description

AI-generated topics

Topics generated by AI based on key concepts in the text.

Entity

Extract entities such as custom, location, person, date, number, organization, date-time, date range, etc. from the text.

Tech Topics

Extract Technology terms from the text

Finance Topics

Extract Financial terms from the text

Medical Topics

Extract Medical/Pharma terms from the text

Custom Topics

Contact us for more info: [email protected]

Topics in Text

The most relevant topics, concepts, discussion points from the conversation are generated based on each sentence/paragraph spoken.

post
Metadata

https://api.marsview.ai/v1/nlp/topics
This method is used to fetch specific Metadata for a particular file_id. It can also be used for long polling to track the progress of compute under the status object.
Request
Response
Request
Headers
Content-Type
optional
string
application/json
appId
optional
string
<sample-app-id>
appSecret
optional
string
<sample-app-secret>
Body Parameters
data.text
optional
boolean
Raw text string on which topics have to be extracted
Response
200: OK
The output consists of two objects. The data object returns the requested metadata if it is computed. The status object shows the current state of the requested metadata.
COMPLETED STATE
COMPLETED STATE
{
"data":{
"global_topics":[
...
{
"topic":"Machine Learning",
"type": "AI Generated",
"start_char":1224,
"end_char":1235
},
{
"topic":"Tesla",
"type": "Entity-Name",
"start_char":2340,
"end_char":2345,
},
...
]
}
}

Response Object Fields

Fields

Description

global_topics

List of global topics extracted from the audio/video file

response

Text of the extracted topic

type

Type of the extracted topic

start_char

Starting character location in the original text

end_char

Ending character location in the original text