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The Next Generation SharePoint: Powered by Text Analytics
This document discusses how text analytics can power the next generation of SharePoint. It begins by outlining common information tasks and how much time they take. It then discusses what text analytics is, how it works, and how it can save time on tasks like search, metadata extraction, and sentiment analysis. It provides examples of text analytics APIs and open source tools. It concludes by demonstrating how text analytics can be integrated into SharePoint using APIs.
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The Next Generation SharePoint: Powered by Text Analytics
- 1. Alyona Medelyan (Pingar) @zelandiya THE NEXT-GENERATION SHAREPOINT: POWERED BY TEXT ANALYTICS
- 2. AGENDA • Information tasks •Text analytics • APIs • Demos • Conclusions
- 3. Information tasks What dothey cost us? How does SharePoint help?
- 4. Avg. hours perweek 14.5 13.3 = $37K year / person 9.6 9.5 8.8 8.3 6.8 6.7 5.6 5.6 4.3 4.2 1 Source: IDC, Hidden Cost of Information (2005)
- 5. SHAREPOINT SAVES TIME Interact with SP from Outlook Create docs collaboratively Customize search configuration Use sites, sets & libraries Define Managed Metadata Configure forms Design Workflow
- 6. Text Analytics What isit and how does it work? What tasks does it solve?
- 7. WHAT IS TEXTANALYTICS? unstructured data Linguistics Search Statistics Data Extraction Text Processing Document Organization Machine Learning Business Intelligence Natural Language Processing Opinion Mining Text Mining
- 8. TEXT ANALYTICS SAVESMORE TIME Compose search reports Extract entities … automatically Mine opinions & sentiment Cluster search results Redact Summarize Generate metadata Fill databases Profanity check
- 9. Text Analytics Software Whatcompanies offer text analytics? What are open source tools like?
- 10. TEXT ANALYTICS: GLOBALPERSPECTIVE User adoption has grown by 25% in 2010 creating an $835 million market because: • Unstructured data grows (ex. social) Text analytics! • Text analytics is central to effective information access • Many successes in NLP: IBM Watson, Wolfram Alpha Full report by Seth Grimes: http://altaplana.com/TA2011
- 11. APPLICATIONS OF TEXTANALYTICS Search & info access 39% Customer experience management 39% Brand management 39% Research 36% Competitive intelligence 33% Customer service 26% E-discovery 15% Life sciences 15% Product design 15% Online commerce 11% Finance 10% Other 9% Content management 8% Insurance & fraud 8% Millitary intelligence 7% Law enforcement 6% Source: http://altaplana.com/TA2011
- 12. SEARCH & INFOACCESS METADATA EXTRACTION Document Easy to extract: Metadata File type, name & location, creation & modification date, authors Difficult to extract: Keywords, people & companies mentioned, suppliers & addresses mentioned
- 13. SEARCH & INFOACCESS KEYWORD EXTRACTION Document Candidates Keywords Hi All, As of today, MetaStock has several new functions. The most important new feature is the ability to display forward heat rate charts. Also, notice that the interface looks different -- this reflects and accommodates the new features. If you have any questions regarding this new version of MetaStock, please contact Bella Santuri.
- 14. SEARCH & INFOACCESS KEYWORD EXTRACTION Document Candidates Keywords Hi All, As of today, MetaStock has several new functions. The most important new feature is the ability to display forward heat rate charts. Also, notice that the interface looks different -- this reflects and accommodates the new features. If you have any questions regarding this new version of MetaStock, please contact Bella Santuri.
- 15. SEARCH & INFOACCESS KEYWORD EXTRACTION Document Candidates Properties Keywords Hi All, As of today, MetaStock has several new functions. Frequency The most important new feature is the ability to Position display forward heat rate charts. Corpus stats Also, notice that the interface looks different -- this Relatedness reflects and accommodates the new features. If you have any questions regarding this new version of MetaStock, please contact Bella Santuri.
- 16. SEARCH & INFOACCESS KEYWORD EXTRACTION Document Candidates Properties Scoring Keywords Hi All, As of today, MetaStock has several new functions. Heuristic The most important new feature is the ability to scoring display forward heat rate charts. Also, notice that the interface looks different -- this Machine reflects and accommodates the new features. learning If you have any questions regarding this new version of MetaStock, please contact Bella Santuri.
- 17. SEARCH & INFOACCESS NAMES EXTRACTION Document Examples Properties Learning Names If you have any questions regarding this new version of MetaStock, please contact Bella Santuri. NLP, Training data Machine Heuristics, (annotations) Learning Text mining
- 18. <SEARCH + TEXTANALYTICS> COMPANIES Pingar, BasisTech, AlchemyAPI, LanguageComputer, OpenCalais, Extractiv
- 19. BRAND & CUSTOMERMANAGEMENT SENTIMENT ANALYSIS Reviews Document Document Visualization Tweets Sentiment Analysis Summary Surveys Naïve approach: Sentiment-words dictionary! Negative Positive BUT: suck fantastic If you are reading this because it terrible excellent is your darling fragrance, please awful awesome wear it at home exclusively, and tape the windows shut. No sentiment words!
- 20. BRAND & CUSTOMERMANAGEMENT SENTIMENT ANALYSIS Reviews Document Document Visualization Tweets Examples Properties Learning Summary Surveys Presence Position Training data Lexicon Machine Part-of-Speech (annotations) induction Learning Negation Generalization Important: Identifying sentiment bearing sentences Attaching sentiment to a topic!
- 21.
- 22. RESEARCH TEXT SUMMARIZATION Address Hi All, Announcement As of today, MetaStock has several new functions. Details The most important new feature is the ability to display forward heat rate charts. More details Also, notice that the interface looks different -- this reflects and accommodates the new features. Conclusion If you have any questions regarding this new version of MetaStock, please contact Bella Santuri. Extractive summary: As of today, MetaStock has several new functions. Sentence compression: MetaStock has several new functions. The new interface looks different. Abstractive summary: MetaStock has new features and a new interface.
- 23.
- 24. COMPETITIVE INTELLIGENCE: ENTITY &ENTITY RELATION EXTRACTION Companies: OpenCalais, Extractiv, Pingar, Evri, AlchemyAPI, Zemanta
- 25. FRAUD INVESTIGATION: NORMALIZATION OFDATES & NAMES Companies: Cicero, BasisTech
- 26. OPEN-SOURCE TOOLS • NLTK– Apache license, Book, Python & academic datasets, nltk.org • LingPipe – Commercial licenses, Tutorials, Coreference & Chinese segment, alias-i.com/lingpipe • OpenNLP – Apache license, Parsing, MaxEnt ML, incubator.apache.org/opennlp • GATE – restricted GPL, Training courses, Applications & framework, gate.ac.uk • Stanford NLP – full GPL, Online docs, Full library, nlp.stanford.edu
- 27. APIs What’s an APIand how does it work? What are the advantages of the API model? Which API is the right one for you?
- 28. API ACCESS a protocol specifies how • SOAP XML needs to be encoded • REST a call is an XML message describing the request includes API authentication calls via a web service API ENGINE SDK usage examples Developer creates An interface that Software engine an application ensures communication solves a specific task
- 29. REST API ACCESSFROM A BROWSER API request http://search.yahooapis.com/WebSearchService/V1/webSe arch?appid=YahooDemo&query=madonna&context=Italian+sc ulptors+and+painters+of+the+renaissance+favored+the+V irgin+Mary+for+inspiration API response
- 30. SOAP API ACCESSFROM VS2010
- 31. SOAP API ACCESSIN POWERSHELL Read complete blog post “Bulk metadata extraction in SharePoint”: http://bit.ly/powershell-migrate
- 32. API = EASYINTEGRATION & FLEXIBILITY • Integrate into existing architecture via any programming language • Improve known flaws in the current system/process • Minimize adoption barriers within the company no or little training required for stuff • Only pay for the features you need • Flexible deployment: • Host API on site = Secure data exchange • Access the API in the cloud = Save on tech support & hardware
- 33. WHICH API ISBEST FOR YOU? I need to take some text and get a list of the important entities/keywords/phrases. Y: Term Extractor API restrictions OpenCalais Supported languages BeliefNetworks Quality of results OpenAmplify Semantic links AlchemyAPI 2nd Synonyms/Duplicates Evri 1st Blog post on API comparison: faganm.com/blog
- 34. HOW TO CHOOSEAN API: • Define a specific task • Think of what features are important • Get prepared: • Subscribe for API keys • Get SDKs • Learn libraries • Find representative data • Build a test framework • Compare results
- 35. METADATA EXTRACTION IN SHAREPOINT Demo Pingar’sadd-on for SharePoint 2010 built using a text analytics API
- 36. INTEGRATING APIS INTO SCANNING Video UsingFuji Xerox SmartConnect and Pingar API to scan documents in batch into SharePoint http://www.youtube.com/watch?v=kluVp25upag
- 38. THE NEXT-GENERATION SHAREPOINT: POWEREDBY TEXT ANALYTICS • What can be automated? • Metadata extraction, Data entry, Opinion mining, Sanitization, Doc approval, Summarization, … • How to integrate text analytics into existing SharePoint applications? • Easy! Via an API • How to find the right text analytics API? • Review what’s available Set up an experiment Compare results
- 39. Thank you toall of our Sponsors
Editor's Notes
- #2 Opening slide please include
- #3 How many hours per week does an average person that uses a computer spends on Searching?What the heck is text analytics, a 101 introduction course…How API work and why they are great for both business people and developers.
- #12 What are your primary applications where text comes into play?