Identifying topics in your documents

The topics app identifies topics in your documents and their relevancy.

Themes are pre-defined categories in which you want to categorize your documents. While topics are extracted from the processed documents.

Prerequisites

The topics.app uses the TopicCandidate entity to identify potential topics. It will automatically run the built-in topics domain to extract these annotations and perform the topic calculus.

Options

TopicsOptions

interface TopicsOptions {
  count?: number;
  threshold?: number;
  ignore_entities?: boolean;
}

with:

Property	Description
count	Maximum number of topics in the results
threshold	Minimal probability, expressed as a percentage, for a topic candidate to be considered a topic
ignore_entities	If enabled, entities such as Person, Country and Company won't be considered topic candidates

Results

TopicsResults

type TopicsResults = TopicsResult[];

TopicsResult

interface TopicsResult {
  name: string;
  relevancy: number;
}

with:

Property	Description
name	Name of the topic
relevancy	Relevancy of the topic within the document

Examples

Identifying topics in your documents

The topics app identifies topics in your documents and their relevancy.

Themes are pre-defined categories in which you want to categorize your documents. While topics are extracted from the processed documents.

Prerequisites

The topics.app uses the TopicCandidate entity to identify potential topics. It will automatically run the built-in topics domain to extract these annotations and perform the topic calculus.

Options

TopicsOptions

interface TopicsOptions {
  count?: number;
  threshold?: number;
  ignore_entities?: boolean;
}

with:

Property	Description
count	Maximum number of topics in the results
threshold	Minimal probability, expressed as a percentage, for a topic candidate to be considered a topic
ignore_entities	If enabled, entities such as Person, Country and Company won't be considered topic candidates

Results

TopicsResults

type TopicsResults = TopicsResult[];

TopicsResult

interface TopicsResult {
  name: string;
  relevancy: number;
}

with:

Property	Description
name	Name of the topic
relevancy	Relevancy of the topic within the document

API

Examples

Using the Topics Identifier object

This script uses the wowool SDK to identify topics in an English sentence, specifying the number of topics to return.

from wowool.sdk import Pipeline
from wowool.topic_identifier import TopicIdentifier

english = Pipeline("english")
number_of_topics = 5
topic_it = TopicIdentifier(language="english", count=number_of_topics)
# display the results of every file, by iterating over every file.
document = topic_it(english("This is the effect of the green house gases"))
for topic in document.topics:
    print(f" - {topic}")

Using the pipeline

This script demonstrates how to use the wowool.sdk's Pipeline class to identify topics in an English text.

from wowool.sdk import Pipeline

pipeline = Pipeline("english,topics.app")
doc = pipeline("Gas supplies to Europe wounded soldiers inside Azovstal steel mill")
print(doc.topics)

License

In both cases you will need to acquirer a license file at https://www.wowool.com

Non-Commercial

This library is licensed under the GNU AGPLv3 for non-commercial use.  
For commercial use, a separate license must be purchased.  

Commercial license Terms

1. Grants the right to use this library in proprietary software.  
2. Requires a valid license key  
3. Redistribution in SaaS requires a commercial license.