Siemens increase sales and reduce service costs through Natural Language Queries of complex, heterogeneous enterprise data

Deployment of USI Answers will save us nearly $10 million dollars this year. We have been able to lower the initial new user training time by more than 50 percent as well as increase efficiency by gaining actionable insight in our data by users across 18 countries.

– Dan Tecuci Siemens Corporate Technology group, Princeton, NJ

Their Goal

Provide a system to allow untrained users who have no knowledge of the underlying information sources to get answers to complex domain-specific questions using natural language.

Their Challenges

  • Poor meta-data
  • Data sources: Dozens of internal and external sources are needed
  • Natural language query processing with an understanding of the domain-specific dictionaries, synonyms, line-of-business and region of business specific abbreviations, and shorthand notation.
  • Structured and un-structured data
  • Data growth – 800% annually growth in information
  • Real-time response to queries – 0.8 seconds
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The Solution

The queries include semantic technology for contextual inferred understanding – for example “show me all active units in the a/p region” requires a contextual understanding of what the ‘units’ are, in this case generators and also to know the business users abbreviate the Asia Pacific region as ‘a/p’. A significant design goal to meet user expectations of responsiveness was to provide answers in less than 1 second regardless of complexity of the query or span of database sizes and locations

Allegrograph Semantic platform:

Energy domain specific concepts and terminology

12,000+ regular expressions used to identify organization names, serial numbers embedded in text

  • Linked Open Data
    • To provide look-up sources of common information that resolve contextual information in documents
    • Connections to public databases in semantic –
      • DBpedia
      • FreeBase
      • GeoNames

Gruff – graph database visualization and query creation

Commercial applications text extraction, open source for phonemes, extraction and open source

The Benefits

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    Reduce the time to find client information by 90%

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    Savings of $10mill in per year in direct and indirect savings

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    Better business insights into customer needs and potential sales