Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
DeepInsights Document Similarity Matrix
By:
Latest Version:
3.0
A solution to find text similarity indices between a set of documents.
Product Overview
Document Similarity solution helps a user find pairwise similarity between documents. This will help in identifying whether two documents have similar verbatim and contextual information. Higher similarity value means documents have very similar contextual information and are written in similar verbatim. This helps in removing duplicate documents from a set.
Key Data
Version
By
Type
Model Package
Highlights
An unsupervised text mining solution to find similarity between documents based on content and context. An intuitive similarity score that ranges from 0 (low similarity) to 1 (high similarity) is computed that can be used to segregate documents belonging to distinct subject groups.
Some of the practical applications for this solution include: 1) Optimization of time taken in searching for relevant information such as de-duplication of search engine results. 2) Grouping documents with similar content. 3) Recommending personalised learning paths for effective knowledge interventions.
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$10.00/hr
running on ml.t2.medium
Model Batch Transform$20.00/hr
running on ml.m5.large
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Realtime Inference$0.056/host/hr
running on ml.t2.medium
SageMaker Batch Transform$0.115/host/hr
running on ml.m5.large
Model Realtime Inference
For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Realtime Inference/hr | |
|---|---|---|
ml.m4.4xlarge | $10.00 | |
ml.g4dn.4xlarge | $10.00 | |
ml.m5.4xlarge | $10.00 | |
ml.m4.16xlarge | $10.00 | |
ml.m5.2xlarge | $10.00 | |
ml.p3.16xlarge | $10.00 | |
ml.r5.large | $10.00 | |
ml.g4dn.2xlarge | $10.00 | |
ml.m4.2xlarge | $10.00 | |
ml.r5.12xlarge | $10.00 | |
ml.c5.2xlarge | $10.00 | |
ml.r5.xlarge | $10.00 | |
ml.p3.2xlarge | $10.00 | |
ml.c4.2xlarge | $10.00 | |
ml.g4dn.12xlarge | $10.00 | |
ml.m4.10xlarge | $10.00 | |
ml.c4.xlarge | $10.00 | |
ml.m5.24xlarge | $10.00 | |
ml.c5.xlarge | $10.00 | |
ml.g4dn.xlarge | $10.00 | |
ml.r5.24xlarge | $10.00 | |
ml.p2.xlarge | $10.00 | |
ml.m5.12xlarge | $10.00 | |
ml.g4dn.16xlarge | $10.00 | |
ml.p2.16xlarge | $10.00 | |
ml.c4.4xlarge | $10.00 | |
ml.r5.4xlarge | $10.00 | |
ml.c5.large | $10.00 | |
ml.m5.xlarge | $10.00 | |
ml.c5.9xlarge | $10.00 | |
ml.m4.xlarge | $10.00 | |
ml.c5.4xlarge | $10.00 | |
ml.p3.8xlarge | $10.00 | |
ml.c4.large | $10.00 | |
ml.m5.large | $10.00 | |
ml.c4.8xlarge | $10.00 | |
ml.p2.8xlarge | $10.00 | |
ml.g4dn.8xlarge | $10.00 | |
ml.t2.xlarge | $10.00 | |
ml.c5.18xlarge | $10.00 | |
ml.t2.large | $10.00 | |
ml.r5.2xlarge | $10.00 | |
ml.t2.medium Vendor Recommended | $10.00 | |
ml.t2.2xlarge | $10.00 |
Usage Information
Fulfillment Methods
Amazon SageMaker
Input
1) The input file should be a zip of text files (.txt) in utf-8 encoding
2) The zipped file can have a maximum of 20 documents
3) The maximum size of the each file should be <= 10KB (1000 lines)
4) Supported Content type: application/zip
Output
1) The output from the model is a csv file, supported content type: text/csv
2) Output file contains a document to document matrix with scores of similarity indices between 0 to 1 interpreted as:
- 0 being least similar
- 1 being most similar
3) Sample output file: |----------------| Document-1 | Document-2 | Document-3 | | Document-1 | 1 | 0.167 | 0.648 | | Document-2 | 0.167 | 1 | 0.070 | | Document-3 | 0.648 | 0.070 | 1 |
Invoking endpoint
AWS CLI Command
If you are using real time inferencing, please create the endpoint first and then use the following command to invoke it:
aws sagemaker-runtime invoke-endpoint --endpoint-name "endpoint-name" --body fileb://input.zip --content-type application/zip --accept text/csv result.csvSubstitute the following parameters:
endpoint-name- name of the inference endpoint where the model is deployedinput.zip- input fileapplication/zip- MIME type of the given input file (above)result.csv- filename where the inference results are written to.
Resources
Additional Resources
End User License Agreement
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Support Information
DeepInsights Document Similarity Matrix
For any assistance, please reach out at:
AWS Infrastructure
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