Sold by: Mphasis
Deployed on AWS
An NLP and knowledge graph based approach to create company profile by aggregating data from multiple sources.
Overview
This solution creates a knowledge graph based on entity-name pairs from data collected from multiple sources of information such as Wikipedia, company's website, CrunchBase etc. This solution creates a graph model of a company's profile based on unstructured data.
Highlights
- This solution selects entity-noun pairs based on section, sub section, paragraph and sentence level hierarchy. Knowledge graph is created by linking these entity-noun pairs where each entity and noun represents nodes of the graph. Connections between these nodes are represented by directed weighted graph edges based on hierarchy as well as phrase level similarity between these nodes.
- The solution uses crawled website data as an input and uses NLP to understand and convert input into graphical format signifying the associated entities along with their relationship.
- Mphasis DeepInsights is a cloud-based cognitive computing platform that offers data extraction & predictive analytics capabilities. Need customized Machine Learning and Deep Learning solutions? Get in touch!
Details
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Delivery method
Latest version
Deployed on AWS
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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 | $20.00 |
ml.t2.medium Inference (Real-Time) Recommended | Model inference on the ml.t2.medium instance type, real-time mode | $10.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $20.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $20.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $20.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $20.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $20.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $20.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $20.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $20.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
Legal
Vendor terms and conditions
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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
This is the second version of the algorithm
Additional details
Inputs
- Summary
This model takes a zip folder with contains the crawled data from any website as an input. Please refer Jupyter notebook where helper code is provided to create the input for the model to use.
- Input MIME type
- application/zip, plain/text
https://github.com/Mphasis-ML-Marketplace/Company-Profile-Creation/blob/main/Input/Input.zip
https://github.com/Mphasis-ML-Marketplace/Company-Profile-Creation/blob/main/Input/Input.zip
Resources
Vendor resources
Support
Vendor support
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