Semantic Search and Text Mining with SQL Server 2012
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Text mining is projected to dominate data mining, and the reasons are evident: we have more text available than numeric data. Microsoft introduced a new technology to SQL Server 2012 called Semantic Search. This session's detailed description and demos give you important information for the enterprise implementation of Tag Index and Document Similarity Index. The demos include a web-based Silverlight application, and content documents from Wikipedia. We'll also look at strategy tips for how to best leverage the new semantic technology with existing Microsoft data mining.
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Semantic Search and Text Mining with SQL Server 2012
- 1. Applied Enterprise Semantic Mining Mark Tabladillo, Ph.D. (MVP, MCAD .NET, MCITP, MCT) PASS SQL Saturday #198 Vancouver BC February 16, 2013
- 2. Photos © 2013 Mark Tabladillo, All Rights Reserved
- 3. Photos © 2013 Mark Tabladillo, All Rights Reserved
- 5. About MarkTab Training and Consulting with Ph.D. – Industrial Engineering, http://marktab.com Georgia Tech Data Mining Resources and Blog at Training and consulting http://marktab.net internationally across many industries – SAS and Microsoft Contributed to peer-reviewed research and legislation Mentoring doctoral dissertations at the accredited University of Phoenix Presenter
- 6. Quick Look My Semantic Search
- 7. Interactive Name three things you want from enterprise text mining
- 8. Introduction SQL Server 2012 has new Programmability Enhancements Statistical Semantic Search File Tables Full-Text Search Improvements These combined technologies make SQL Server 2012 a strong contender in text mining
- 9. Outline Why Microsoft is competitive for data mining Definitions: what is text mining? History: how Microsoft’s semantic search was born What is inside semantic search Logical model Demos Performance Microsoft Resources
- 10. Why Microsoft is Competitive for Data Mining Based on 2012 and 2013 Surveys
- 11. Gartner 2013 Magic Quadrant for Business Intelligence and Analytics Platforms Retrieved from http://www.gartner.com/technology/reprints.do?id=1-1DZLPEH&ct=130207&st=sb – February 5, 2013
- 12. Gartner 2013 Magic Quadrant for Data Warehouse Database Management Systems Retrieved from http://www.gartner.com/technology/reprints.do?id=1-1DU2VD4&ct=130131&st=sb – January 31, 2013
- 14. Definitions What is text mining?
- 15. Definition Data mining is the automated or semi-automated process of discovering patterns in data Text mining is the automated or semi-automated process of discovering patterns from textual data Machine learning is the development and optimization of algorithms for automated or semi-automated pattern discovery
- 16. Purposes Phrase Goal “Data Mining” Inform actionable decisions “Text Mining” “Machine Determine best performing Learning” algorithm
- 17. MarkTab Decision Cycle GO Synthesis Analysis (art) (science) Science needs science fiction -- MarkTab
- 18. MarkTab Decision Cycle GO Synthesis Analysis (art) (science)
- 19. History How Microsoft’s semantic search came to be
- 20. History July 2008 Microsoft purchases Powerset for US$100 Million Google Dismisses Semantic Search http://venturebeat.com/2008/06/26/microsoft-to-buy-semantic-search-engine- powerset-for-100m-plus/ http://www.forbes.com/2008/07/01/powerset-msft-search-tech-intel- cx_ag_0701powerset.html
- 21. History March 2009 Google announces “snippets” as relevant to search The media picks this story up as “semantic search” http://googleblog.blogspot.com/2009/03/two-new-improvements-to-google- results.html#!/2009/03/two-new-improvements-to-google-results.html
- 22. History February 2012 Google announces Knowledge Graph, an explicit application of semantic search http://mashable.com/2012/02/13/google-knowledge-graph-change-search/
- 23. History April 2012 Microsoft purchases 800+ patents from AOL for US$1 Billion Among the patents are semantic search and metadata querying – older than Google http://www.theregister.co.uk/2012/04/09/aol_microsoft_patent_deal/
- 24. What is inside Semantic Search Text Mining introduced for SQL Server 2012
- 25. Future: Most data is Text Two Research Types • Quantitative research = data mining • Qualitative research = text mining The future is combining both
- 26. Statistical Semantic Search Comprises some aspects of text mining Identifies statistically relevant key phrases Based on these phrases, can identify (by score) similar documents
- 27. FileTables Built on existing SQL Server FILESTREAM technology Files and documents Stored in special tables in SQL Server Accessed if they were stored in the file system
- 28. Full-Text Search Enhancements Property search: search on tagged properties (such as author or title) Customizable NEAR: find words or phrases close to one another New Word Breakers and Stemmers (for many languages)
- 29. Logical Model How semantic search works
- 30. From Documents to Output Office Varchar PDF NVarchar Rowset Output with Scores
- 31. (iFilter Required) iFilters Full-Text Documents Keyword Index “FTI” Semantic Key Phrase Semantic Index – Semantic Document Database Tag Index Similarity Index “DSI” “TI”
- 32. Languages Currently Supported Traditional Chinese Simplified Chinese German British English English Portuguese French Chinese (Hong Kong SAR, PRC) Italian Spanish Brazilian Chinese (Singapore) Russian Chinese (Macau SAR) Swedish
- 33. Phases of Semantic Indexing Full Text Keyword Index “FTI” Semantic Document Similarity Index “DSI” Semantic Key Phrase Index – Tag Index “TI” http://msdn.microsoft.com/en-us/library/gg492085.aspx#SemanticIndexing
- 34. Interactive Demo SQL Server Management Studio
- 35. Semantic Search and SQL Server Data Mining SQL Server Data Tools: data mining plus text mining
- 37. Integrated Full Text Search (iFTS) Improved Performance and Scale: Scale-up to 350M documents for storage and search iFTS query performance 7-10 times faster than in SQL Server 2008 Worst-case iFTS query response times less than 3 sec for corpus Similar or better than main database search competitors (2012, Michael Rys, Microsoft)
- 38. Linear Scale of FTI/TI/DSI First known linearly scaling end-to-end Search and Semantic product in the industry Time in Seconds vs. Number of Documents (2011 – K. Mukerjee, T. Porter, S. Gherman – Microsoft)
- 39. Text Mining References Video http://channel9.msdn.com/Shows/DataBound/DataBound-Episode-2-Semantic- Search http://www.microsoftpdc.com/2009/SVR32 Semantic Search (Books Online) – explains the demo http://msdn.microsoft.com/en-us/library/gg492075.aspx Paper http://users.cis.fiu.edu/~lzhen001/activities/KDD2011Program/docs/p213.pdf
- 41. Software SQL Server 2012 Enterprise (includes database engine, Analysis Services, SSMS and SSDT) http://www.microsoft.com/sqlserver/en/us/get-sql-server/try-it.aspx Microsoft Office 2012 Professional http://office.microsoft.com/en-us/try
- 42. Organizations Professional Association for SQL Server http://www.sqlpass.org Atlanta MDF http://www.atlantamdf.com/ Atlanta Microsoft BI Users Group http://www.meetup.com/Atlanta-Microsoft- Business-Intelligence-Users/ PASS Business Analytics Conference http://www.passbaconference.com Microsoft TechEd North America http://northamerica.msteched.com/
- 44. Conclusion SQL Server Data Mining 2012 provides data mining and semantic search The core technology allows document similarity matching The results can be combined with SQL Server Data Mining (such as Association Analysis)
- 45. Connect Data Mining Resources and blog http://marktab.net Data Mining Training and Consulting (especially Microsoft and SAS) http://marktab.com