Sold by: MphasisÂ
Deployed on AWS
ML based solution which classifies airline reviews into positive and negative sentiment categories.
Overview
This solution classifies airline reviews into positive and negative sentiments. It uses text analysis, natural language processing, machine learning techniques to predict sentiment classes for airline reviews. It also generates two word clouds: one each for positive and negative sentiment reviews. It automates the manual effort to analyze airline reviews and helps generate faster actionable insights around airline services.
Highlights
- Airline reviews sentiment analyzer takes airline reviews as input and predicts the category of each review as positive or negative. This solution uses Natural Language Processing to process the reviews, and classifies them into positive or negative sentiment categories.
- Airline reviews sentiment analyzer provides sentiments for each input review. It generates two word clouds: one for positive sentiment reviews and one for negative sentiment reviews. It also provides a bar chart explaining the distribution of positive and negative sentiments over reviews.
- Mphasis HyperGraf is an omni-channel customer 360 analytics solution. Need customized Deep Learning/NLP solutions? Get in touch!
Details
Sold by
Delivery method
Latest version
Deployed on AWS
Unlock automation with AI agent solutions
Fast-track AI initiatives with agents, tools, and solutions from AWS Partners.
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.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $16.00 |
ml.m5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.xlarge instance type, real-time mode | $8.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $16.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $16.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $16.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $16.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $16.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $16.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $16.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $16.00 |
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
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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 version 3.1.
Additional details
Inputs
- Summary
- The input dataset should be in csv format.
- The column names in input file should be:
- text: airline reviews only in English Language.
- input file should not contain more than 20 reviews.
- Input MIME type
- text/csv, text/plain, application/zip
https://github.com/Mphasis-ML-Marketplace/Airline-Reviews-Sentiment-Analyzer/tree/main/input
https://github.com/Mphasis-ML-Marketplace/Airline-Reviews-Sentiment-Analyzer/tree/main/input
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
text | airline reviews only in English Language | Type: FreeText | Yes |
Resources
Vendor resources
Support
Vendor support
For any assistance reach out to us at:
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.
Similar products
Machine Learning based solution which classifies tweets about airlines into positive, neutral and negative sentiment categories.
The Infosys Cobalt Airline Cloud is a comprehensive cloud-based platform designed specifically for the airline industry. It offers cloud-native solutions for business differentiation and innovation catering to various stakeholders. It provides an integrated ecosystem that enhances agility, elasticity, efficiency, and resilience in airline operations. The platform addresses key industry challenges by offering solutions for personalized travel experiences, disruption management, dynamic schedule adjustments, decarbonization efforts, and cargo demand. It leverages digital technologies and advanced analytics to improve passenger journeys, operational efficiency, and sustainability in the aviation sector
Optimize your airline FinOps with this AI-Driven solution. Reach a deeper understanding of costs across all key airline segments through a collaboration between finance and engineering teams. Our solution optimizes sales channels, reduces operational costs, and streamlines flight management expenses.
Modernizing Airline Operations through Research-Driven Design based on AWS Cloud Services, Cloud-Native Development, and AWS Innovation
Customer reviews
No customer reviews yet
Be the first to review this product . We've partnered with PeerSpot to gather customer feedback. You can share your experience by writing or recording a review, or scheduling a call with a PeerSpot analyst.