Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. This deck provides how to build your own text analytics using Amazon Comprehend and integration with other AWS services. On top of that, this deck also provides an introduction to Amazon Lex.

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Donnie Prakoso, MSc
AWS Technology Evangelist, ASEAN
Text Analytics Workload with
Amazon Comprehend
AWS User Group Meetup
@donnieprakoso

2. © 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Hello, World.
Donnie Prakoso, MSc
AWS Technology Evangelist, ASEAN
@donnieprakoso
donnieprakoso
• Speak in Go and Python
• Machine Learning and Serverless
• I AWS User Groups

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© 2018, Amazon Web Services, Inc. or Its Affiliates. All rights reserved.
Let’s Discuss Something
• Why do we need text analytics?
• What are the examples of the use cases?
• How Amazon Comprehend can help
you?
• Demo + API and architecture diagram
example
https://bit.ly/aws-donnie-serverless-text-analytics

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Why do we need text
analytics?

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Enabling The Possibility for These Use Cases
• News Media
• Brand trends, correlating events
• Customer engagement
• Call center, issue triage, social media analytics
• Records and research
• Actionable document-centric processes, understand patterns

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AWS Machine Learning Services

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FRAMEWORKS AND INTERFACES
AI for data scientists
KERAS
Frameworks Interfaces
APPLICATION SERVICES
AI for everyone
P O L L Y R E K O G N I T I O N C O M P R E H E N DL E X R E K O G N I T I O N
V I D E O
T R A N S C R I B E T R A N S L A T E
PLATFORM SERVICES
AI for engineers
AMAZON
SAGEMAKER

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G e t S t a r t e d w i t h
A W S M L A p p l i c a t i o n S e r v i c e s
POLLY REKOGNITION COMPREHENDLEX REKOGNITION
VIDEO
TRANSCRIBE TRANSLATE

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Sentiment Entities Languages Key phrases Topic modeling
POWERED BY DEEP
LEARNING
Amazon Comprehend
Discover insights and relationships in text

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Entities
Key Phrases
Language
Sentiment
Amazon
Comprehend
Amazon Comprehend
Discover insights and relationships in text

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A m a z o n . c o m , I n c . i s l o c a t e d
i n S e a t t l e , W A a n d w a s
f o u n d e d J u l y 5 t h , 1 9 9 4 b y
J e f f B e z o s . O u r c u s t o m e r s
l o v e b u y i n g e v e r y t h i n g f r o m
b o o k s t o b l e n d e r s a t g r e a t
p r i c e s
N a m e d E n t i t i e s
• A m a z o n . c o m : O r g a n i z a t i o n
• S e a t t l e , W A : L o c a t i o n
• J u l y 5 t h , 1 9 9 4 : D a t e
• J e f f B e z o s : P e r s o n
K e y p h r a s e s
• O u r c u s t o m e r s
• b o o k s
• b l e n d e r s
• g r e a t p r i c e s
S e n t i m e n t
• P o s i t i v e
L a n g u a g e
• E n g l i s h
Text Analysis

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Synchronous
• DetectDominantLanguage and BatchDetectDominantLanguage – to detect
the dominant language in a document. We can detect up to 100 languages.
• DetectEntities and Batch DetectEntities – to detect the entities, such as persons
or places, in the document.
• DetectKeyPhrases and Batch DetectKeyPhrases – to detect key noun phrases
that are most indicative of the content.
• DetectSentiment and Batch DetectSentiment – to detect the emotional
sentiment, positive, negative, mixed, or neutral, of a document.
API Summary - Synchronous

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Demo
Twitter Sentiment Analysis w/
Amazon Comprehend

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Twitter
Search API
Analyze social media postings and comments
AWS
Lambda
Amazon
S3
AWS IoT
Amazon
DynamoDB

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Twitter
Stream API
Organize and classify customer feedback and look for common patterns.
Visualize results in Amazon QuickSight
Amazon
Kinesis
Amazon
Athena
Amazon
S3
AWS
Lambda

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Amazon Comprehend
Customer Feedback Analytics

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Amazon Comprehend
STORM
WORLD SERIES
STOCK MARKET
WASHINGTON
LIBRARY OF
NEWS ARTICLES
Amazon
Comprehend
Topic Modelling

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Topic Modeling
Document Topic Proportion
Doc.txt 0 .89
Doc.txt 1 .67
Doc.txt 2 .91
Topic Term Weight
0 Washington .89
1 Silicon Valley .67
2 Roasting .91
Keywords Topic Groups Document Relationship to Topics

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Asynchronous
• StartTopicDetection – to start a topic modeling job
• ListTopicDetection – to list all your submitted jobs
• DescribeTopicDetection –to get progress status and
information about each submitted job
API Summary - Asynchronous

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Demo
Classifying Customer
Feedback

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Comprehend + AWS = Scale Text Analytics
Amazon Kinesis
Amazon EMR
Amazon Redshift
Amazon EMR
• Semantic
• Rich Filtering
• Grouping, Trends
• Joining, Correlating
• Clustering
• Graph, Search
• Near real-time
• Alerts
Amazon S3
Articles, Documents
Social Media, Support
Amazon Aurora

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Amazon Comprehend
Knowledge Management and Discovery

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Ideas Are Welcome
Content Personalization: Customers are using Comprehend NLP output to understand related documents
based on entities, phrases or even topic similarities for trends analysis, to drive content personalization and
recommendations
Semantic Search: Customers using Amazon Comprehend to index entities for boosting and ranking
search results.
Intelligent data warehouse: Customers are using Amazon Comprehend to query unstructured data in
relational databases, processing data within the data lake (S3) and then inserting it back into the data
warehouse
Social Analytics: Customers are using Amazon Comprehend to ingest, process and analyze trends from
entities and sentiment from social media posts across Twitter and Facebook.
Information management: Customers are using Amazon Comprehend for indexing and finding related
content for enterprise information management and various internal business processes including
compliance and IT.

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Amazon Lex
Scale
Business Logic
SecurityAnalytics
Text to Speech
Speech to Intent
End to
End
Native support &
maintains context
One-click
deployment
Completely managed
service
Native integration
with AWS Lambda
Encrypted
data in transit
& at rest
Monitor and
improve
Amazon Polly
integrated into API
ASR + NLU integrated
into one API
Dialog Management Deployment

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Amazon Lex
Informational
Bots
Chatbots for
everyday consumer
requests
Application
Bots
Build powerful
interfaces to mobile
applications
News updates
Weather information
Game scores ….
Book tickets
Order food
Manage bank accounts ….
Enterprise Productivity
Bots
Streamline enterprise
work activities and
improve efficiencies
Check sales numbers
Marketing performance
Inventory status ….
Internet of Things
(IoT) Bots
Enable conversational
interfaces for device
interactions
Wearables
Appliances
Auto ….
Contact Center
Bots
Chatbots for
customer service IVR
Account inquiries
Bill payment
Service update ….
Use cases

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Intents
A particular goal that the
user wants to achieve
Utterances
Spoken or typed phrases
that invoke your intent
Slots
Data the user must provide to fulfill the
intent
Prompts
Questions that ask the user to input
data
Fulfillment
The business logic required to fulfill the
user’s intent
BookHotel

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Amazon Lex Customers

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Build On!
Donnie Prakoso
@donnieprakoso