Microsoft Enterprise Search - featuring FAST ESP

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    Microsoft Enterprise Search - featuring FAST ESP - Presentation Transcript

    1. Microsoft Enterprise Search
      Paul Loefstedt
      Microsoft Technical Solutions Provider
    2. Selected Microsoft FAST CustomersPowering the World’s Largest Search Innovation Network
      2
    3. Where FAST ESP is Key
      SCALABILITY
      SEARCH QUALITY
      Billions of documents index size
      Thousands of queries per second
      Indexing performance: thousands of documents per second
      Query latency < 1 second
      Expressive relevance model
      Contextual Search
      Deep navigation
      Approximate search
      Matching
      Business rules
      Security
      Linguistic depth and breadth, fully configurable and customizable
      • 82 languages
      • Spell check, lemmatization, synonyms
      • Entity extraction (20 entities ootb, custom entities)
      Configurable and customizable
      Pioneered SOA – pluggability
      Fusing content, data & rich media
      APPLICABILITY
      FLEXIBILITY
      3
    4. Typical SharePoint Search applications
      Internal Applications
      Customer-facing Apps
      Standard intranet search
      Content mgmt applications
      People & expertise search
      Enterprise 2.0 apps
      Structured data search
      Standard site search
    5. Typical FAST ESP applications
      Internal Applications
      Customer-facing Apps
      Research portals
      Unified customer views
      Competitive intelligence
      Federated search network
      Structured data search
      Compliance & risk mgmt
      e-Commerce
      Classifieds
      Premium content portals
      Directories
      Advertising
      Customer self-service
    6. User Experience
      Search Engine
      Content Processing
      ScaleFAST ESP is designed for extreme scale across 3 dimensions.
      • Guaranteed sub-second response times at thousands of queries per second
      • Fine tuning for index freshness
      • Designed for content volume up to 10 billion docs or 40 petabytes
      • Best for content volume less than 20-30M docs.
      FAST ESP
      Linear Scaling Architecture
      • Search engine instances are grouped in clusters.
      • Rows are used for query scaling.
      • Columns are used for content volume scaling.
      Query Volume
      Content Volume
      • Navigators
      • Taxonomy
      • Unsupervised clustering
      • Personalization
      • Recommendations
      • Geospatial search
      • Deep federation
      • Collections
      • Search profiles
      • Search business center
      • FAST ESP scope search
      • Sophisticated content retrieval and document processing
      User Experience
      Search Engine
      Content Processing
      ESP enables a "conversational” experience
      • Standard Search Center
      • Search web parts
      • Search tabs
      • OpenSearch federation
      • Best bets
      • Keyword synonyms
      • SharePoint search scopes
    7. Extensible Document Processing
      Format
      Conversion
      Language
      Detection
      Lemmas
      (forms, tenses)
      Spell-
      checking
      Synonyms
      Entities
      (company,
      geography)
      Taxonomy
      Classification
      Custom
      PLUG-IN
      Speechtagger
      Sentiment
      Analysis
      News
      PARIS (Reuters) - Venus Williamsraced into the second round of the $11.25 million French Open Monday, brushing aside Bianka Lamade, 6-3, 6-3, in 65 minutes.
      The Wimbledon and U.S. Openchampion, seeded second, breezed past the German on a blustery center court to become the first seed to advance at Roland Garros. "I love being here, I love the French Open and more than anything I'd love to do well here," the American said.
      A first roundloser last year, Williams is hoping to progress beyond the quarter-finals for the first time in her career.
       Index
      Scopifier
      Real-Time Content Refinement
      8
    8. 9
      Tunable Relevancy
      Transparent
      Tunable
      Field & keyword weight
      Freshness, authority, completeness (proximity), distance, quality, context, statistics (TF/IDF)
      Sentiment
      Flexible
      Defensible
      • Dictionary & configurable thesaurus
      • Advanced lemmatization
      • Spell checking & advanced phrase recognition
      • Anti-phrasing
      • Auto completion
      • 77 languages
      • Advanced support for Chinese, Japanese, and Korean
      • Offensive content filter
      • Entity extraction
      • Relationship extraction
      • Linguistics Studio
      User Experience
      Search Engine
      Content Processing
      Advanced LinguisticsFAST ESP offers sophisticated linguistic s for improved relevancy.
      • Basic linguistic processing, including language detection, stemming, & word breaking
      • Basic thesaurus based on XML entries in flat file
      • Basic “Did you mean?” based on index entries
      • Elimination of noise words
      • 36 languages
    9. Text Mining & Information Extraction
      <Category>FINANCIAL</ Category >
      <Author>George Stein</ Author >
      BC-dynegy-enron-offer-update5
      Dynegy May Offer at Least $8 Bln to Acquire Enron (Update5)
      By George Stein
      SOURCEc.2001 Bloomberg News
      BODY
      <Company>Dynegy Inc</Company>
      <Person>Roger Hamilton</Person>
      <Company>John Hancock Advisers Inc.</Company>
      <PersonPositionCompany> 
      <OFFLENOFFSET="3576" LENGTH="63" />
       <Person>RogerHamilton</Person>
      <Position>moneymanager</Position>
      <Company>John Hancock Advisers Inc.</Company>
      </PersonPositionCompany>
      …….
      ``Dynegy has to act fast,'' said Roger Hamilton, a money manager with John Hancock Advisers Inc., which sold its Enron shares in recent weeks. ``If Enron can't get financing and its bonds go to junk, they lose counterparties and their marvelous business vanishes.''
      Moody's Investors Service lowered its rating on Enron's bonds to ``Baa2'' and Standard & Poor's cut the debt to ``BBB.'' in the past two weeks.
      ……
      Fact
      <Company>Enron Corp</Company>
      <Company>Moody's Investors Service</Company>
      <CreditRating> 
      <OFFLENOFFSET="3814" LENGTH="61" /> 
      <Company_Source>Moody'sInvestorsService</Company_Source> 
      <Company_Rated>EnronCorp</Company_Rated>
      <Trend>downgraded</Trend> <Rank_New>Baa2</Rank_New> 
      <__Type>bonds</__Type> 
      </CreditRating>
      Event
      11
    10. Title:
      Body:
      Author:
      John Smith, George Johnsen
      Creation date:
      13th of January, 2006
      COLLECTION
      DOCUMENT
      SUB-DOCUMENT
      ENTITY
      <sentence>
      1 GEOFFREY BIBLE, recently retired CEO of Philip Morris International. Born in Sydney in 1937, he now lives in New York.
      </sentence>
      <person>
      GEOFFREY BIBLE
      </person>
      12
      Information Scopes
    11. Contextual MetadataNavigation Precision
      13
    12. Demo!

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