Gartner Research

Google, Apple Siri and IBM Watson: The Future of Natural-Language Question Answering in Your Enterprise

Published: 28 June 2013

ID: G00250733

Analyst(s): Jamie Popkin


NLQA systems such as Siri, Google and Watson employ natural-language processing and computational linguistics to directly answer user questions. By reducing the time to answer, these virtual assistants, search engines and cognitive systems offer improved business value.

Table Of Contents

Summary of Findings


  • What Is a Natural-Language Question-Answering System?
    • What Problems Do Natural-Language Question-Answering Systems Solve?
    • What Kinds of Answers Do Natural-Language Question-Answering Systems Provide?
    • How Text Summarization Works
    • How Do Question-Answering Systems Work?
  • What Types of Natural-Language Question-Answering Systems Are Commercially Available, and What Problems Do They Solve?
    • Commercially Available Systems
    • What Problems Are Solved by Each Type of NLQA System?
  • Where Is Natural-Language Question-Answering Technology Headed?
    • Cloud-Based Architectural Concerns
    • Integration Capabilities With Enterprise Systems
    • Search Engine Futures
    • Virtual Assistant Futures
    • Cognitive System Futures
    • Graph Databases, Memory-Based Reasoning, Continuous Transaction, and Business Analytics for Data and Pattern Discovery
    • Voice Recognition Technology
  • Strengths
  • Weaknesses

The Details

  • Question-Answering and Text Summarization Technology
    • Factoid Question Answering
    • Text Summarization
  • Google, Siri and Watson Technical Architecture Overview
    • Google's Technical Architecture
    • Siri's Technical Architecture
    • Watson's Technical Architecture

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