MeshLabs
Text Analytics
©	
  2013	
  MeshLabs	
  So0ware	
  Private	
  Limited	
  
Confiden<al	
  
About US
2	
  
Featured Customers:
Provider	
  of	
  text	
  analy<cs	
  so0ware	
  products	
  
Informa<on	
  Management	...
Text, Text, Everywhere…
3	
  
4	
  
Too much volume and variety	
   Missed	
  Opportuni1es	
  
Product Managers
Customer Insight Managers
Research Analy...
Text Analytics
5	
  
Linguis<cs	
  
Sta<s<cs	
  
Seman<cs	
  
powerful	
  technology	
  
to	
  automa<cally…	
  
Ingest	
 ...
How it Works
6	
  
1	
  
v  Connectors to Enterprise Content Stores,
Facebook, Twitter etc.
v  Crawlers for getting data...
Key Use Cases
7	
  
Informa<on	
  
Extrac<on	
  
“How	
  do	
  I	
  
extract	
  key	
  
informa<on	
  
from	
  CRM	
  
Not...
Customer Testimonial
8	
  
“We	
  partnered	
  with	
  MeshLabs	
  because	
  of	
  their	
  unique	
  ability	
  to	
  
c...
Our Product –
eZi CORE™ Text Analytics Engine
9	
  
MeshLabs eZi CORE ™
eZi Semantic
Search ™
eZi Reco ™
eZi Connectors ™ ...
Core Capabilities
10	
  
ü 	
  Data	
  Acquisi<on	
  and	
  Inges<on	
  
ü 	
  Text	
  Prepara<on	
  	
  	
  
ü 	
  Nam...
Data Acquisition and Ingestion
11	
  
•  File	
  System	
  
•  SharePoint	
  
•  Alfresco	
  
•  Web	
  Crawler	
  
•  Twi...
12	
  
Out-of-the-box Taxonomies
Airline	
  Industry	
  
Automobile	
  
Industry	
  
Banking	
  
Company	
  -­‐	
  
Indust...
13	
  
Dashboards & Reports
Sentiment Analysis
14	
  
•  Feature-­‐Based	
  Sen<ment	
  Analysis	
  supported	
  
•  Lexicon	
  based	
  analysis	
  
...
Feature Detection
15	
  
•  Features:	
  Extrac<on	
  of	
  Context	
  Relevant	
  
Nouns	
  /	
  Noun	
  Phrases	
  	
  
...
Contact Us
16	
  
sales@meshlabsinc.com	
  
www.meshlabsinc.com	
  
@meshlabs	
  
linkedin.com/company/meshlabs	
  
facebo...
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Presentation by Meshlabs at Zensar #TechShowcase - An iSPIRT ProductNation initiative.

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Presentation by Meshlabs at Zensar #TechShowcase - An iSPIRT ProductNation initiative.. Bangalore based firm; has a text analytics platform. Listens to all stake holders and unlocks the hidden value via text analytics.

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Presentation by Meshlabs at Zensar #TechShowcase - An iSPIRT ProductNation initiative.

  1. 1. MeshLabs Text Analytics ©  2013  MeshLabs  So0ware  Private  Limited   Confiden<al  
  2. 2. About US 2   Featured Customers: Provider  of  text  analy<cs  so0ware  products   Informa<on  Management  |  Customer  Experience  Management    |  Business  Intelligence  |  Regulatory  Compliance   ü  On-­‐premise   ü  SaaS   ü  API   ü  Unified  Content  Access   ü  En<ty  Extrac<on  /  Tagging   ü  Categoriza<on   ü  Summariza<on   ü  Recommenda<on   ü  Faceted  Search   ü  Sen<ment  Analysis   ü  Dashboard  &  Repor<ng  
  3. 3. Text, Text, Everywhere… 3  
  4. 4. 4   Too much volume and variety   Missed  Opportuni1es   Product Managers Customer Insight Managers Research Analysts Customer Care Reps Sales & Marketing Leaders HR Leaders Senior Executives   Cost / Quality concerns over manual methods  Current BI tools won’t work   Structured data only and too complicated   And Not a Single Insight. Multiple Channels, Sources and Types Limited Analysis, Ad hoc, Scalability Issues   Topline and Bottom-line Impact  
  5. 5. Text Analytics 5   Linguis<cs   Sta<s<cs   Seman<cs   powerful  technology   to  automa<cally…   Ingest  all  text  data/content   Extract  valuable  assets   Deliver  ac<onable  insights   1   2   3  
  6. 6. How it Works 6   1   v  Connectors to Enterprise Content Stores, Facebook, Twitter etc. v  Crawlers for getting data from websites v  Upload files & documents – Excel, Word, PDF etc. 2   Process your data – Extract entities, classify, cluster, and score sentiment v  NLP – Natural Language Processing v  Taxonomies & Custom Ontologies v  Machine Learning 3   Analyze output - dashboards, reports, workflows, and alerts v  Dashboards v  Charts & Reports v  Exports Gather your data – Text (Unstructured) and Structured
  7. 7. Key Use Cases 7   Informa<on   Extrac<on   “How  do  I   extract  key   informa<on   from  CRM   Notes  to   predict  cross-­‐ sell  &  up-­‐sell   opportuni<es”   Opinion   Mining   “  How  do  I  gain   ac<onable   insights  from   market  &   customer     interac<ons   across   channels?  ”   Auto-­‐ Categoriza<on   “  As  a  retailer,   how  do  I   display   categorized     lis<ngs  in  the   most  efficient   manner?  “   Intelligent   Agents   “  With  so   much   informa<on   overload,  how   do  I  transform   the   effec<veness   of  my   knowledge   workers?  “  
  8. 8. Customer Testimonial 8   “We  partnered  with  MeshLabs  because  of  their  unique  ability  to   connect  to  and  integrate  all  types  of  data  and  content  from  our   communi<es.  This  allows  us  to  bring  game  changing  analy<cs   and  repor<ng  to  our  clients  enabling  them  to  discover  new   insights  to  refine  messaging,  cra0  an  innova<on  strategy,  and   improve  customer  loyalty.”   THOMAS  FINKLE   CEO,  Think  Passenger,  Inc.   Passenger  is  a  leader  in   providing  Market  Research   Online  Communi1es  PlaKorm  
  9. 9. Our Product – eZi CORE™ Text Analytics Engine 9   MeshLabs eZi CORE ™ eZi Semantic Search ™ eZi Reco ™ eZi Connectors ™ and Crawlers Microsoft SharePoint, Outlook, Alfresco Enterprise Content Web Content eZi Sentiment Analyzer ™ Entity Extractor POS Tagging Classifier Clustering Rules Engine Inference / Reasoner Unified Semantic Index / Triple Store Search Interface Dashboards APIs Custom Solutions •  On-­‐Premise   •  SaaS   •  API  
  10. 10. Core Capabilities 10   ü   Data  Acquisi<on  and  Inges<on   ü   Text  Prepara<on       ü   Named  En<ty  Extrac<on   ü   Auto-­‐Categoriza<on   ü   Feature  Extrac<on   ü   Sen<ment  Analysis   ü   Summariza<on   ü   Recommenda<on   ü   Faceted  Search   ü   Dashboard  &  Repor<ng  
  11. 11. Data Acquisition and Ingestion 11   •  File  System   •  SharePoint   •  Alfresco   •  Web  Crawler   •  TwiUer   •  Facebook   •  Blogs   •  YouTube   •  Discussion  Forums   •  Yahoo  Answers   •  Hadoop  File  System  (S3,   HDFS  etc.)   •  Databases  (any  JDBC   compliant  database)    
  12. 12. 12   Out-of-the-box Taxonomies Airline  Industry   Automobile   Industry   Banking   Company  -­‐   Industry   Classifica<on   Computers  and   Laptops   Corporate  Social   Responsibility   Cosme<cs   Customer  Service   -­‐  Generic   Hotels   Human  Resources   -­‐  Voice  of   Employee   Product-­‐Category   Classifica<on   Real  Estate   Retail   Smart  Phones  and   Tablets   Telecom   Travel  
  13. 13. 13   Dashboards & Reports
  14. 14. Sentiment Analysis 14   •  Feature-­‐Based  Sen<ment  Analysis  supported   •  Lexicon  based  analysis   §  Per-­‐domain  lexicon  supported   •  Uses  deep  parsing  to     §  Iden<fy  features   §  Associa<on  of  nega<on  and  suppor<ng  words   •  Mul<ple  levels  of  sen<ment  scoring  supported   •  Sen<ment  Analysis  done  at  sentence  fragment  scope   •  Weighted  rollup  of  sen<ment  score  provides  overall   view  
  15. 15. Feature Detection 15   •  Features:  Extrac<on  of  Context  Relevant   Nouns  /  Noun  Phrases     ü  Noun  Phrase  Extrac<on   ü  Deep  Parsing  and  Lexical  Chaining   ü  Sen<ment  Scoring    at  Feature-­‐level   “The  coffee  was  bad,  but  the  sandwich  was  good.”     •  Featureless  Sen<ment  Score  –  Neutral   •  Featured-­‐based:   ü  Overall  Sen<ment  –  Neutral   ü  Coffee  –  Nega<ve   ü  Sandwich  -­‐  Posi<ve  
  16. 16. Contact Us 16   sales@meshlabsinc.com   www.meshlabsinc.com   @meshlabs   linkedin.com/company/meshlabs   facebook.com/meshlabs   USA:  1-­‐602-­‐617-­‐9370    |    India:  91-­‐9986004572  
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