rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: The
    title: answer machine
  title info:
    title: Synthesis digital library of engineering and computer science
  name:
    name part: Feldman, Susan.
    role:
      role term: creator
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: cau
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xvii, 119 pages) : illustrations
  abstract: The Answer Machine is a practical, non-technical guide to the technologies behind information seeking and analysis. It introduces search and content analytics to software buyers, knowledge managers, and searchers who want to understand and design effective online environments. The book describes how search evolved from an expert-only to an end user tool. It provides an overview of search engines, categorization and clustering, natural language processing, content analytics, and visualization technologies. Detailed profiles for Web search, eCommerce search, eDiscovery, and enterprise search contrast the types of users, uses, tasks, technologies, and interaction designs for each. These variables shape each application, although the underlying technologies are the same. Types of information tasks and the trade-offs between precision and recall, time, volume and precision, and privacy vs. personalization are discussed within this context. The book examines trends toward convenient, context-aware computing, big data and analytics technologies, conversational systems, and answer machines. The Answer Machine explores IBM Watson's Deep QA technology and describes how it is used to answer health care and Jeopardy questions. The book concludes by discussing the implications of these advances: how they will change the way we run our businesses, practice medicine, govern, or conduct our lives in the digital age.
  table of contents: 1. Introduction -- 1.1 Why information seeking is so important to us --
  table of contents: 2. The query process and barriers to finding information online -- 2.1 The query process -- 2.2 Query problems --
  table of contents: 3. Online search: an evolution -- 3.1 History -- 3.2 The shifting information landscape: 2000-2012 -- 3.2.1 End users as searchers -- 3.2.2 Changes in information seeking -- 3.2.3 State of the art today --
  table of contents: 4. Search and discovery technologies: an overview -- 4.1 Online information access systems -- 4.2 Search and discovery technologies -- 4.3 Types of search systems -- 4.4 The information retrieval process -- 4.5 Search and content analytics -- 4.6 Collecting information for searching or analysis -- 4.7 Search engines: the index and the matching engine -- 4.8 Presenting the results: what is "relevance?" -- 4.8.1 Beyond the document list -- 4.9 Categorization, classification, clustering, and faceted search -- 4.9.1 Automatic vs. manual categorization -- 4.10 Natural language processing (NLP) and content analytics -- 4.11 Time, sentiment, and geo-location -- 4.12 NLP in information retrieval -- 4.12.1 Some common uses of NLP -- 4.13 Multilingual and cross language search, gisting, and translation -- 4.14 Knowledge bases -- 4.14.1 Rich media search --
  table of contents: 5. Information access: a spectrum of needs and uses -- 5.1 Information tasks -- 5.2 Information seekers -- 5.3 Finding the right search technology -- 5.3.1 First questions -- 5.3.2 Information needs assessment checklist -- 5.4 Trade-offs in search and content technologies -- 5.5 Search and content analytics technologies: sample use cases -- 5.5.1 Web search -- 5.5.2 eCommerce search -- 5.5.3 eDiscovery search -- 5.5.4 Enterprise search -- 5.6 Search and content analytics in the enterprise -- 5.6.1 Consumer vs. business search -- 5.7 Trends in enterprise search -- 5.7.1 Unified information access -- 5.7.2 InfoApps and search-based applications -- 5.7.3 Opinion,trend, and sentiment monitoring -- 5.7.4 Question answering systems -- 5.7.5 Site search -- 5.7.6 Mobile search -- 5.8 Enterprise search systems in summary --
  table of contents: 6. Future tense: the next era in information access and discovery -- 6.1 Shift to probabilistic computing -- 6.2 Learning systems: machine learning, adaptive systems, predictive analytics, and inferencing -- 6.3 Big data and analytics -- 6.4 Improved information interaction: contextual awareness, conversational systems, and visualization -- 6.5 Complex, highly integrated information platforms --
  table of contents: 7. Answer machines -- 7.1 What's an answer machine? -- 7.1.1 Question definition -- 7.1.2 Interaction design -- 7.1.3 Analytics and adaptive learning -- 7.1.4 Complex, highly integrated information platforms -- 7.2 IBM's Watson: an answer machine case study -- 7.2.1 Watson for Jeopardy -- 7.2.2 What's under the hood? -- 7.3 Answer machines and the future -- 7.3.1 What answer machines can't do -- 7.3.2 Implications -- 7.4 Conclusion --
  table of contents: Bibliography -- Author's biography -- Index.
  note: Susan E. Feldman.
  note: Electronic resource.
  note: Includes bibliographical references (pages 111-114) and index.
  subject:
    topic: Question-answering systems
  subject:
    topic: Research
    topic: Technological innovations
  subject:
    topic: Information behavior
  subject:
    topic: Watson (Computer)
  subject:
    topic: COMPUTERS / Enterprise Applications / Business Intelligence Tools
  subject:
    topic: COMPUTERS / Intelligence (AI) & Semantics
  subject:
    topic: search engines
  subject:
    topic: content analytics
  subject:
    topic: user interaction
  subject:
    topic: natural language processing
  subject:
    topic: contextual awareness
  subject:
    topic: probabilistic computing
  subject:
    topic: big data
  subject:
    topic: analytics
  subject:
    topic: conversational systems
  subject:
    topic: enterprise search
  subject:
    topic: Web search
  subject:
    topic: eDiscovery
  subject:
    topic: eCommerce search
  subject:
    topic: unified information access
  subject:
    topic: InfoApps
  subject:
    topic: machine learning
  subject:
    topic: adaptive systems
  subject:
    topic: answer machines
  subject:
    topic: IBM Watson
  classification: Q180.55 .I45 F45 2012
  classification: 006.3
  related item:
    title info:
      title: Answer machine
    name:
      name part: Feldman, Susan.
    origin info:
      publisher: San Rafael : Morgan & Claypool, 2012
    identifier: (OCoLC)801929124
  related item:
    title info:
      title: Synthesis lectures on information concepts, retrieval, and services ; #23
  identifier: 9781608459353 (electronic bk.)
  identifier: 1608459357 (electronic bk.)
  identifier: 9781608459346 (print)
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: AZS
    record creation date: 121008
    record change date: 20190404202447.0
    record identifier: in00003338090