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  • I4S+
  • Industry 4.0
    • Automation
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enterprise search

Improving Central Information Access in Enterprise Search

Improving Central Information Access in Enterprise Search

A self-learning search approach
Norbert Gronau ORCID Icon, Julian Bahrs, Kirstin Peters
The self-learning search engine improves the search for relevant information in enterprises by using a profile of the searcher and a context, that has to be chosen for each search request. Case-based reasoning is used to figure out which information sources contain relevant information for the given combination of profile and context. These information sources are further preferred in enterprise search.
Industrie Management | Volume 24 | 2008 | Edition 4 | Pages 9-12
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  • I4S+
  • Industry 4.0
    • Automation
    • Digital Twin
    • Factory Planning
    • Industry 4.0
    • Internet of Things
    • Lean Production
    • Sustainability
    • Manufacturing Systems
    • Adaptability
  • Artificial Intelligence
  • Functions
    • Start-up Management
    • Maintenance
    • Logistics
    • Assembly
    • Product Development
    • Production Planning
    • Production Control
    • Process Management
    • Quality Management
    • Risk Management
    • Safety
  • Tools
    • Additive Manufacturing
    • Analytics
    • Augmented Reality
    • Blockchain
    • Modularization
    • Training
    • Robotics
    • Sensors
    • Simulation
    • Software
  • Management
    • Services
    • Dynamics
    • Energy Efficiency
    • Leadership
    • Business Models
    • Innovation
    • SME
    • Management
    • Product Piracy
    • Resource Efficiency
    • Strategy
    • Profitability
  • Journal
    • Current Issue
    • Editorial Calendar
    • Editorial Board
    • Order in Print
    • All E-Journals
    • Annual Table of Contents
    • List of Reviewers
  • Information
    • Books
    • Find 4IR Consultants
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    • Find ERP Consultants
    • Find ERP Software
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