Overview
Topic Modeling is a powerful text analysis tool for discovering hidden patterns and trends in large collections of text documents. Leveraging the power of the advanced transorfmer based models, this solution employs state-of-the-art natural language processing techniques and machine learning algorithms to provide exceptional topic modeling results. The comprehensive text preprocessing pipeline, including tokenization, part-of-speech tagging, and lemmatization, ensures clean and normalized input data for analysis. With an easy-to-use interface, this solution is accessible to users of all skill levels, enabling them to quickly retrieve dominant topics, topic probabilities, and top words for each topic, gaining valuable insights into their text data.
Highlights
- Topic Modeling is a machine learning approach that uses unsupervised learning to identify clusters of similar words in a document. It presents a powerful text-mining technique that enables the discovery of concealed semantic structures within a body of text.
- This solution can be used to create solutions to determine the topic of a set of documents based on the content, generate meaningful insights from the similar words in the entire corpus of text data and extract a summary of the underlying text and discover important contexts from the text.
- Need more machine learning, deep learning, NLP and Quantum Computing solutions. Reach out to us at Harman DTS.
Details
Delivery method
Latest version
Deployed on AWS
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Features and programs
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $50.00 |
ml.t2.medium Inference (Real-Time) Recommended | Model inference on the ml.t2.medium instance type, real-time mode | $5.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $50.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $50.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $50.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $50.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $50.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $50.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $50.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $50.00 |
Vendor refund policy
We do not provide any usage related refunds at this time.
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Bug fixes and feature updates
Additional details
Inputs
- Summary
Input is a json file containing the text document to be analyzed
- Input MIME type
- application/json
https://github.com/HDTS-user/eNova-topic-modeling/blob/main/input/test.json
https://github.com/HDTS-user/eNova-topic-modeling/blob/main/input/test.json
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
id | A unique id for the text document | Type: FreeText | Yes |
ABSTRACT | The text document for which topic modeling is required | Type: FreeText
Limitations: Please provide a minimum of 3 sentences per document to be analyzed | Yes |
Resources
Support
Vendor support
Business hours email support marketplaceSupp@harman.comÂ
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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