Sold by: MphasisÂ
Deployed on AWS
This is a NLP based solution which can detect up to 8 aspects and their sentiments from online product reviews for storage devices.
Overview
This solution identifies the various aspects and their corresponding sentiment from online product reviews for storage devices. The following 8 aspects are identified: price, storage capacity, size, build quality, ease of use, speed(read and write), support and, thermals and the 3 sentiments identified are: positive, negative and, neutral. This enables companies to easily identify and evaluate the aspects being reviewed. The information can be used to assess changes in consumer priorities and focus on trending aspects by identifying which aspects garner positive reviews and which don't. Companies can use this solution for providing inputs to advertising and marketing campaigns and product design.
Highlights
- This solution is trained on a large publicly available dataset of router reviews. Solution uses semi-supervised latent dirichlet allocation algorithm to identify 8 aspects related to storage devices and a State of the Art model to classify the sentiment for the respecitve aspects.
- This solution can be used by e-commerce companies, manufacturers, and retailers to identify the aspects and respective sentiments from online customer reviews.
- Mphasis HyperGraf is an Omni-channel customer 360 analytics solution.Mphasis HyperGraf is an omni-channel customer 360 analytics solution. Need customized Deep Learning/NLP solutions? Get in touch!
Details
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Delivery method
Latest version
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
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.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large 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.
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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 performance enhancement
Additional details
Inputs
- Summary
Each text file should have 1 review with maximum of 2000 characters. Should have only ASCII characters. Works only for English language inputs.
- Input MIME type
- text/plain
https://github.com/Mphasis-ML-Marketplace/Aspect-Based-Sentiment-Storage-Devices/blob/main/input/sample.txt
https://github.com/Mphasis-ML-Marketplace/Aspect-Based-Sentiment-Storage-Devices/blob/main/input/sample.txt
Resources
Vendor resources
Support
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