La Búsqueda Empresarial cambiará la forma en que los usuarios interactúan con la información

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2 La Búsqueda Empresarial cambiará la forma en que los usuarios interactúan con la información Search en toda la Organización Proporcionando las mejores experiencias a los usuarios Cambiará la forma en cómo las empresas manejan sus negocios

3 People Search Content Recoge entrada del usuario, muestra resultados Construye el índice, devuelve resultados Recupera contenido, prepara para indexación User Experience Search Engine Content Processing Escalabilidad User experience Procesamiento de contenido Search en datos estructurados Relevancia Lingüística avanzada

4 Query Volume FAST ESP diseñado para escalar de forma casi ilimitada Tiempos de respuesta garantizados < 1 seg atendiendo miles de queries por segundo Tuning avanzado del Índice Diseñado para volúmenes de contenido de hasta M de items o 40 PB User Experience Search Engine Content Processing FAST ESP Linear Scaling Architecture Rendimiento óptimo hasta M de items Search engine instances are grouped in clusters. Rows are used for query scaling. Columns are used for content volume scaling. Content Volume

5 FAST ESP permite una "experiencia de búsqueda conversacional" Navigators Taxonomy Unsupervised clustering Personalization Recommendations and Featured Content Geospatial search Deep Federation Collections Search Profiles Search Business Center FAST ESP scope search Sophisticated content retrieval and processing User Experience Search Engine Content Processing Standard Search Center Search web parts Search tabs OpenSearch federation Best bets Keyword synonyms SharePoint search scopes

6 FAST ESP ofrece capacidades sofisticadas de proceso de documentos Index schemas Index profiles FAST ESP scope search Full-featured crawler Support for content push Document processing engine & flexible pipeline Entity extraction pipeline modules User Experience Search Engine Content Processing FAST ESP Document Pipeline Crawl rules Crawl schedules

7 FAST ESP es ideal para búsquedas con queries en datos estructurados con fines específicos Predictable, sub-second response times for ad-hoc queries on structured data Exact counts on navigators Advanced sorting Advanced ranking FAST ESP scope search Many connectors for structured data sources Data cleansing capabilities ETL integration User Experience Search Engine Content Processing Basic sorting Basic ranking BDC profile pages No-code approach to structured data connectors using the BDC

8 FAST ESP incluye varias opciones para el tuning de relevancia Query analysis using pipeline Navigators, taxonomies & clustering facilitate conversation User profiles Advanced linguistic processing Advanced sorting and ranking Dynamic Teasers Sophisticated ranking model based on freshness, authority, quality, proximity & content Expressive queries with FAST Query Language (FQL) XRANK Document processing engine & document pipelines Advanced linguistic processing User Experience Search Engine Content Processing Basic sorting Basic ranking Sort by social distance for people search results Teasers Strong out-of-the-box relevance for internal apps Authoritative sites Property weighting Keyword query language and SQL query language Basic linguistic processing, including language detection, stemming, & word breaking

9 Freshness How fresh is the document compared to the time of the query? Completeness How well does the query match superior contexts like the title or the url? Example: query= Mexico, Is Mexico or University of New Mexico best? Authority Is the document considered an authority for this query? Examples: Web link cardinality, article references, product revenue, page impressions, Statistics How well does the contents of this document on overall match the query? Examples: Proximity, context weights, tf-idf,++ Quality What is the quality of the document? Examples: Bitrate? KHz?... Distance Where s the nearest x from where I am?

10 A relevancy framework: Not a black box relevancy model Robust: Over a dozen attributes available for tuning Proximity, field, keyword, freshness, business rules, authority, quality, link cardinality, distance, context weights, statistics (tf-idf), degree of linguistics normalization Flexible: Open and tunable rank-profiles allow you to mix attributes to create the relevancy model right for your application. Rank-Profile: A Relevancy Mixing Board Authority: Freshness: Proximity: Context: Body: Description URL: Keywords: Title:

11 Rank-Profile: Internet Authority: Freshness: Proximity: Context: Body: Description URL: Keywords: Title: Rank-Profile: News Authority: Freshness: Proximity: Context: Body: Description URL: Keywords: Title: Rank-Profile: Site Search Authority: Freshness: Proximity: Context: Body: Description URL: Keywords: Title:

12 FAST ESP ofrece lingüística sofisticada Dictionary & configurable thesaurus Advanced lemmatization Spell checking & advanced phrase recognition Anti-phrasing Auto completion 80 languages Linguistics Studio Advanced support for Chinese, Japanese, and Korean Offensive content filter Entity extraction Relationship extraction User Experience Search Engine Content Processing Basic thesaurus based on XML entries in flat file Did you mean? based on index entries Elimination of noise words 36 languages Basic linguistic processing, including language detection, stemming, & word breaking

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14 The core mechanism in FAST ESP5 for recognizing and tagging structure in context. Politics of Ukraine In July 1994, Leonid Kuchma was elected as Ukraine's second president in free and fair elections. Kuchma was reelected in November 1999 to another five-year term, with 56 % percent of the vote. International observers criticized aspects of the election, especially slanted media coverage; however, the outcome of the vote was not called into question. In March 2002, Ukraine held its most recent parliamentary elections, which were characterized by the Organization for Security and Cooperation in Europe (OSCE) as flawed, but an improvement over the 1998 elections. The pro-presidential For a United Ukraine bloc won the largest number of seats, followed by the reformist Our Ukraine bloc of former Prime Minister Viktor Yushchenko, and the Communist Party. There are 450 seats in parliament, with half chosen from party lists by proportional vote and half from individual constituencies. PIPELINE Person Location End of sentence Date Base = XX End of paragraph Acronym

15 FAST ESP supports identification of the entities below. Rather than extracting the entities as global meta information, ESP allows these entities to be tagged in their position in the text. Entity extractors will add attributes in addition to tagging the entity itself. For instance, the Company extractor will add an attribute containing the company ticker symbol. Semantic Entities Person Company Location Job title Newspaper University Date Price Measurement Acronym Airline Car File name ISBN Phone Zip code Ticker Time Structural Entities Paragraph Sentence Quotation

16 Paragraph Sentence CONTENT PIPELINE... Rome is the capital of Italy... Sentence President Clinton was born William Jefferson Blythe IV on August 19, 1946 Data Normalization Data Extraction XMLGeneration Cerebral infarct / medicine Cerebral infarct / biology Cerebral infarct Cerebral infarcts Phrasing Topic classification Lemmatization Infarctus cérébral Cerebral infarct / conferences Doc type classification Cerebral infarct Character normalization Refinement Ambiguous queries Cerebral infarkt Serebral infarct Cetebral ingarct Spellchecking Phonetic match Thesaurus support Synonymy Apoplexy Apoplectic insult Stroke Cerebral disease Infarction QUERY PIPELINE Ortographic Morphological Vocabulary Variations Domain Models

17 Query: What is Cerebral infarkt? Tokenizer Cerebral infarct Cerebral infarct What is Infarctus cérébral Spellcheck Phrasing Antiphrase Normalize Cerebral infarcts Apoplexy Apoplectic insult Stroke Cerebral disease Infarction NLQ Lemmas Synonyms PLUG-IN Thesaurus Geography Use Medline collection Rank profile = Citation quality Adaptive Evaluation Modified query Many named query pipelines Accepts user plug-ins Selectable at query-time

18 Query: Do you have a LCD monitor under $900? Tokenizer Spellcheck Phrasing Do you have a Antiphrase Normalize Under $900? price < 900 LCD monitors TFT monitor Flat TV Plasma TV YES! X = LCD monitor NLQ Lemmas Synonyms Thesaurus PLUG-IN BUY( X ) Use Product collection Rank profile = Profit margin Geography Adaptive Evaluation Modified query

19 FAST AdVisor FAST ImPulse FAST msearch Client Specific Search Apps FAST Marketrac FAST ProPublish Client Specific Search Apps FAST InStream Client Specific Search Apps BUSINESS SEGMENTS ebusiness Knowledge Enablement Application Enablement SEARCH DERIVATIVE APPLICATIONS (SDAs) ENTERPRISE SEARCH PLATFORM (ESP) FAST ESP Legacy Data (e.g. ISAM, VSAM, IMS) Applications (e.g. ERM, CRM, Help Desk) RDBMS (JDBC, ODBC, SQLNet, DW, DM) DMS/ Systems (e.g. M Soft CMS, Documentum, Notes, Exchange) XML Files (e.g. Word, Excel, pdf, images, mp3) Portals (e.g. WebSphere, WebLogic) Private Webs (e.g. news feeds, Intranets) WWW (HTML, WML, JavaScript) Multimedia (e.g. images, sounds, video) Message Queues (e.g. TIBCO, MQ-Series) Direct Push STRUCTURED UNSTRUCTURED REAL-TIME

20 Market Management Solutions Risk Management Solutions Surveillance & Enforcement Solutions Information Management Solutions ecommerce Solutions Online Media Solutions Mobile Solutions Corporate Operations Solutions Embedded Application Solutions Options FAST ESP Legacy Data Applications RDBMS DMS, CMS, Files Rich Media XML Elements, Portals Internet RSS Feeds, XPath Data Streams

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22 Consulta en tiempo real de minería de datos La mayor agencia del mundo de noticias Resultados con FAST ESP Vigila el uso de material protegido por derechos de autor, con lo cual evita los malos usos e incrementa las ganancias. Actualmente utiliza FAST en 7 proyectos de integración internos.

23 Ámbito comercial (CRM): Análisis de Sentimiento Banca: Tratamiento de prácticas ilícitas: rastreo s, llamadas, tono de la conversación, etc Seguros: Detección de Fraude: frases y expresiones Fuerzas de Seguridad del Estado: rastreo de actividades, geolocalización de sospechosos, búsqueda en imágenes y vídeos

24 McMillan, John, Samuel McMillan, John, Samuel McMillan, John, S McMillan, John McMillan, J, Samuel McMillan, J, S McMillan, Samuel McMillan, John, Samuel McMillan, Samuel, John Samuel, McMillan, John John Samuel McMillan MacMillan, John, Samuel

25 Mohammed (Muhammad, Muhammed, Mohammad, Mohamed, Mohamet, Mohamad, Mihammad,.) (Muhammad, Muhammed, Mohammad, Mohamed)

26 GEORGE

27 microsoft.com / EnterpriseSearch

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