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Bangalore, Indi A Platform for Text Analytics Vaklipi http:// www.vaklipi.com Aiaioo Labs vaklipi.com

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Page 1: Vaklipi Text Analytics Tools

Bangalore, India

A Platform for Text Analytics

Vaklipi

http://www.vaklipi.com

Aiaioo Labs vaklipi.com

Page 2: Vaklipi Text Analytics Tools

Aiaioo Labs

• Research Lab– Natural Language Processing– Machine Learning– Information Retrieval

• Vaklipi– Vaklipi is the brand under which our text

processing tools are distributed.– Vak means Speech or Spoken Language– Lipi means Writing or Written Language

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Page 3: Vaklipi Text Analytics Tools

What can Vaklipi help you get out of text?

The opportunities vary by vertical:

1. Aerospace / Defense / Automotive – Compliance process automation / Technical specification standardization / Competitive intelligence and customer feedback processing

2. Healthcare / Life sciences – Reporting / Storing, retrieving and analyzing patents and publications / Extraction of actionable insights from research and competitive intelligence

3. Legal and Government – Legal and administrative filings / Case document and administrative record management, e-discovery / Extraction of facts from legal and administrative documents (land records, case files)

4. FMCG – Routine reports, invoicing, tax documents / Sentiment and Intention Analysis / Call center insights

5. BFSI – Reporting / Churn and product propensity analysis / Forms processing, customer care, monitoring, fraud detection

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Page 4: Vaklipi Text Analytics Tools

How do we unlockthe value in “text”?

Output Text / Store and Analyse Text / Ingest Text

d. Vaklipi Generation Tools

a. Vaklipi Extraction Toolsb. Vaklipi Classification Tools

c. Vaklipi Exploration Tools

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Page 5: Vaklipi Text Analytics Tools

Vaklipi Extraction Tools

“Extraction”

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Page 6: Vaklipi Text Analytics Tools

a. Vaklipi Extraction Tools

Use Cases:

1. Customer Service2. Land Records3. Mergers and Acquisitions4. Sentiment Analysis5. Intention Analysis6. Sales Lead List Extraction

(4, 5 and 6 are supported out of the box, while1, 2 and 3 will require customization)

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Page 7: Vaklipi Text Analytics Tools

Use Case 1: Customer Service

Let’s say you have some text … … and a database or spreadsheet with columns

“John Chambers of Springfield, MAreported a problem with the clutchon his Ford Ranger purchased inBoston, MA in 2005.”

… and you have to fill in the database fieldsfrom the information in the text …

Reporter Location (of Reporter)

Product

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Page 8: Vaklipi Text Analytics Tools

Use Case 1: Customer Service

“John Chambers of Springfield, MAreported a problem with the clutchon his Ford Ranger purchased inBoston, MA in 2005.”

Entities are pieces of text that could go into the fields in the database.

Relations connect the entities that belong in a row.

Reporter Location Product

John Chambers

Springfield, MA

Ford Ranger

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Page 9: Vaklipi Text Analytics Tools

Use Case 2: Government – Land Records

Let’s say you have some text … … and a database or spreadsheet with columns

“Property K45L234(lot 23-24) in Wake Countyof 3000 sq ftwas sold to James Fischeron 3-30-1997 …”

… and you have to fill in the database fieldsfrom the information in the text …

Title# Lot County

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Page 10: Vaklipi Text Analytics Tools

Use Case 3: Legal Domain – Mergers/Acquisitions

Let’s say you have some text … … and a database or spreadsheet with columns

“Acme Financials, a subsidiaryof Lehman Sisters, was acquiredby John Doe Corp on 5/26/2001.”

… and you have to fill in the database fieldsfrom the information in the text …

Acquirer Acquired Date

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Page 11: Vaklipi Text Analytics Tools

Use Case 4: Sentiment Analysis

Let’s say you have some text … … and a database or spreadsheet with columns

“The Canon 3F model is sturdyand excellent for studio use.”

… and you have to fill in the database fieldsfrom the information in the text …

Product Sentiment Purpose

Canon 3F Positive Studio Use

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Page 12: Vaklipi Text Analytics Tools

Use Case 4: Sentiment Analysis

Live demo: http://www.aiaioo.com:8080/annotator-0.1/automation/demoView/1

Aiaioo Labs vaklipi.com

Page 13: Vaklipi Text Analytics Tools

Use Case 4:Sentiment Analysis is available in many languages

Live demo: http://www.aiaioo.com:8080/annotator-0.1/automation/demoView/1

Aiaioo Labs vaklipi.com

Page 14: Vaklipi Text Analytics Tools

Use Case 5: Intent Analysis

Let’s say you have some text … … and a database or spreadsheet with columns

“I want to learn more aboutthe premium plan you havefor frequent fliers.”

… and you have to fill in the database fieldsfrom the information in the text …

Product Intent Constraint

Premium plan

Inquire Frequent fliers

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Page 15: Vaklipi Text Analytics Tools

Use Case 5: Intent Analysis

Live demo: http://www.aiaioo.com:8080/annotator-0.1/automation/demoView/2

Aiaioo Labs vaklipi.com

Page 16: Vaklipi Text Analytics Tools

Use Case 6: Sales Lead List Extraction

Let’s say you have some text … … and a database or spreadsheet with columns

“Tim Cook is the CEO of Apple a firm in the computer industry…”

… and you have to build a leads list of CEOs by industry …

CEO Firm Industry

Tim Cook Apple Computers

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Page 17: Vaklipi Text Analytics Tools

Use Case 6:Sales Function – Sales Lead List Extraction

Video demonstration: http://selasdia.com/lead-finder/(Selasdia is the brand of a robotic sales assistant developed on the Vaklipi platform)

Aiaioo Labs vaklipi.com

Page 18: Vaklipi Text Analytics Tools

Use Case 6: CXO and Email Finder

Video demonstration: http://selasdia.com/cxo-finder/(Selasdia is the brand of a robotic sales assistant developed on the Vaklipi platform)

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Page 19: Vaklipi Text Analytics Tools

Vaklipi Classification Tools

Type = “Tools”

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Page 20: Vaklipi Text Analytics Tools

b. Vaklipi Classification Tools

Use Cases:

1. Problem Routing (Assignment)2. Topic Classification3. Sentiment Classification4. Subjectivity Classification5. Intention Classification6. Language Identification7. Gender Identification

(3, 4, 5, 6 and 7 are supported out of the box, while1 and 2 will require customization)

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Page 21: Vaklipi Text Analytics Tools

Use Case 1: Problem Routing

Let’s say you have some text … … and you want to mark it as one of …

“John Chambers of Springfield, MAreported a problem with the clutchon his Ford Ranger purchased inBoston, MA in 2005.”

… and so route to customer service or sales

Report

Inquiry

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Page 22: Vaklipi Text Analytics Tools

Use Case 2: Topic Classification

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Let’s say you have a news item… … and you want to mark it as one of …

“Luxembourg Foreign Minister Jean Asselbornhas called for Hungary to be suspended oreven expelled from the European Unionbecause of its "massive violation" of EUfundamental values..”

… and so decide the news category

Politics

Sports

Page 23: Vaklipi Text Analytics Tools

Use Case 3: Sentiment Classification

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Let’s say you have a review … … and you want to mark it as one of …

“WOW...that's all I can say. I've been waiting forthis one to come out on Blu-ray for quite awhile...and I can truly say, it was worth the wait. Finally,this movie looks like it did in the theater...the colors,details and clarity are amazing...”

… and so decide the news category

Positive

Negative

Page 24: Vaklipi Text Analytics Tools

Use Case 4: Subjectivity Classification

You can use Vaklipi to decide if there is an opinion/sentiment in the sentence in the first place …

“I am sad that Steve Jobs died.” Subjective“Steve Jobs died.” Objective

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Page 25: Vaklipi Text Analytics Tools

Use Case 5: Intent Classification

We provided an intent classifier with Vaklipi …

“Who has a typewriter for sale?”

• Purchase intention

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Page 26: Vaklipi Text Analytics Tools

Use Case 6: Language Identification

(A very accurate language identifier is provided with Vaklipi) …Live demo:

http://www.aiaioo.com:8080/annotator-0.1/automation/demoView/6

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Page 27: Vaklipi Text Analytics Tools

Use Case 7: Gender Identification

(A multilingual gender identifier is provided with Vaklipi) …

Male Female

Arun

Ashwin

Akshata

Aparna

Out-of-the-box models available

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Page 28: Vaklipi Text Analytics Tools

All the above use cases illustrate a technique called Classification

There are two types of classification supported by the Vaklipi platform:1. Classification using Machine Learning2. Classification using Linguistic Resources (Gazetteers)

Advantages of using the Vaklipi platform:3. Several pre-built classifiers available out of the box4. Support for rapid development of new classifiers

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Page 29: Vaklipi Text Analytics Tools

Vaklipi Exploration Tools

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Page 30: Vaklipi Text Analytics Tools

c. Vaklipi Exploration Tools

Use Cases:

1. Automatic Label Generation for Grouping / Retrieval2. Frequent Issue Detection3. Key Issue Detection4. Churn Prediction5. Product Propensity Analysis6. Shift Detection7. Summarization8. Bootstrapping Extraction Tools

(All are supported out of the box – the raw data will need to be set up for the tool but no training data is needed)

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Page 31: Vaklipi Text Analytics Tools

Use Case 1: Data Organization

ABSTRACTA challenging problem faced by researchers and developers of distributed real-time and embedded (DRE) systems is devising and implementing effective adaptive resource management strategies that can meet end-to-end quality of service (QoS) requirements in varying operational conditions. This paper presents two contributions to research in adaptive resource management for DRE systems.

How do you label/organize the following research abstract?

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Page 32: Vaklipi Text Analytics Tools

Use Case 1: Data Organization

1. adaptive resource management2. distributed real-time embedded system3. end-to-end quality of service4. service end-to-end quality5. hybrid adaptive resourcemanagement middleware6. hybrid control technique7. real-time video distribution system8. real-time corba specification9. video encoding/decoding10. resource reservation mechanism11. dynamic environment

These tags that were chosen bya human.

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Page 33: Vaklipi Text Analytics Tools

Use Case 1: Data Organization

1. resource utilization2. base station3. qos requirements4. dre multimedia5. a/v streaming service6. frame rate7. end-to-end qos requirements8. adaptive resource management9. network bandwidth10. application qos11. picture resolution

These tags that were chosen bya machine.

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Page 34: Vaklipi Text Analytics Tools

Use Case 2: Frequent Issue Detection

The customer complained about delays in processing incoming international payments ...

Textual Events

I helped the customer recover his lost password after he was locked out of his account ...

Method:Take a bunch of textual events such as these and reduce them to a set of issues such as:

a) international payment delaysb) account lockout

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Page 35: Vaklipi Text Analytics Tools

Use Case 3: Key Issue Detection

The customer complained about delays in processing incoming international payments ...

Textual Events

I helped the customer recover his lost password after he was locked out of his account ...

Method:Take a bunch of textual events such as these that are correlated with adverse business events and reduce them to a set of issues such as:

a) payment delayb) account lockout

Account balance < Rs. 1,00,000

Adverse Business Events

Online account usage frequency drops to 0 for 3 months.

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Page 36: Vaklipi Text Analytics Tools

Use Case 4: Churn Analysis

Applications to Churn Analysis

The customer is having a lot of issues with the online portal.

Textual Events

The customer was locked out of his account again ...

Account balance < Rs. 1,00,000

Adverse Business Events

Online account usage frequency drops to 0 for 3 months.

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Page 37: Vaklipi Text Analytics Tools

Use Case 5: Purchase Propensity Analysis

Applications to Purchase Propensity Analysis

The customer inquired about accessing investment banking services.

Textual Events

Customer requested a credit line.

New investment made

Propitious Business Events

Increased safe use of credit line.

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Page 38: Vaklipi Text Analytics Tools

Use Cases 6: Shift Detection

Shift detection is a form of trend analysis useful for marketing or planning.

Category Leaders: 20101) Marketo2) Radian63) Pardot4) Alchemy5) Hubspot6) Act-On7) Lexalytics

Category Leaders:20151) Hubspot2) Marketo3) Act-On4) Salesforce5) IBM6) Oracle7) Adobe

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Page 39: Vaklipi Text Analytics Tools

Use Case 7: Summarizing Feedback

Applications to processing large interaction streams

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Page 40: Vaklipi Text Analytics Tools

Vaklipi Generation Tools

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d. Vaklipi Generation Tools

Use Cases:

1. Text Entry Assistance2. Smart User Interfaces3. Customer Support Assistance4. OCR/Speech Output Correction5. Question Answering6. Summarization

(These require training data and extensive customization and are mostly used where operational efficiency is important)

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Page 42: Vaklipi Text Analytics Tools

Use Case 1: Text Entry Assistance (Auto-Suggest)How do you help a text entry operator make fewer mistakes?

Vaklipi allows you to develop models which predict what someone isabout to type.

These can be integrated into user interfaces to create auto-suggest systems.

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Page 43: Vaklipi Text Analytics Tools

Use Case 2: Smart User Interfaces

How do you guide a user to use a machine learning tool so that it makes fewer mistakes?

Vaklipi allows you to develop models that can guide usage intelligently.These require an integration with user interfaces.

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Page 44: Vaklipi Text Analytics Tools

Use Case 3: Customer Support AssistanceHow do you guide a customer support person to answer questions faster?

Vaklipi allows you to develop answer retrieval and customization systems thatcan make the job of a CSR easier.

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Page 45: Vaklipi Text Analytics Tools

Use Case 4: OCR/Speech Output Correction

How do you correct the output of a machine learning tool so that it makes fewer mistakes?

Vaklipi allows you to develop models that can correct othermachine learning algorithms.

Source Channel

Decoder

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Page 46: Vaklipi Text Analytics Tools

Use Case 5:Answering Questions

First you classify the question into one of 3 types… and these are…

“Do you ship your cars to Boston, MA?”

“Who is the CEO of Apple?”

“Why is the sky blue?”

Yes/No questions

Factoid questions

Non-factoid questions

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Page 47: Vaklipi Text Analytics Tools

Use Case 5:Answering Questions

Look for answers in databases that you created using entity / relationship extraction

“Do you ship your cars to Boston, MA?”

“Who is the CEO of Apple?”

“Why is the sky blue?”

Product Ships To

Cars USA

CEO Firm

Tim Cook

Apple

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Page 48: Vaklipi Text Analytics Tools

Use Case 5:Answering Questions (Who is the CEO of Adobe?)

Video Demo: http://selasdia.com/cxo-finder/

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Page 49: Vaklipi Text Analytics Tools

Use Case 6: Summarization

Useful for processing / distilling large interaction streams

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Page 50: Vaklipi Text Analytics Tools

THE END

Bangalore, India

http://www.vaklipi.com

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