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 ...

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. Presentation Transcript

  • 1. MeshLabs Text Analytics ©  2013  MeshLabs  So0ware  Private  Limited   Confiden<al  
  • 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. Text, Text, Everywhere… 3  
  • 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. 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. 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. 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. 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. 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. 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. 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   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   Dashboards & Reports
  • 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. 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. 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