Improving Enterprise Wide Search in Large Engineering Multinationals: A Linguistic Comparison of the Structures of Internet-Search and Enterprise-Search Queries

  • David Edward JonesEmail author
  • Yifan Xie
  • Chris McMahon
  • Marting Dotter
  • Nicolas Chanchevrier
  • Ben Hicks
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 467)


Understanding how users formulate search queries can allow the development of search engines that are tailored to the way users search and thus improve the knowledge discovery process, a key challenge for Product Lifecycle Management (PLM) systems.

This paper presents part-of-speech (POS) statistical analysis on two sets of ‘Top 500’ search query lists in order to compare Internet search with enterprise search with the aim of understanding how enterprise search queries differ from Internet search queries. The Internet queries were obtained from the keyword research company and covers the month of January 2015. Enterprise search logs were obtained from a large multinational engineering organization and represent the first six months of 2014.

The results show enterprise search users are far more likely to search using nouns, with 97 % of queries containing at least one noun. This compares to 89 % for Internet users. 60 % of enterprise queries are single nouns compared to 38 % for Internet search users. In total, enterprise queries fell into 41 lexical classes (noun-noun/adjective-noun/etc.) whilst Internet search contained 95 classes. Of those 41 classes only 12 % contained no nouns, compared to 21 % for Internet search. 80 % of the enterprise search queries can be covered by just four Lexical classes compared to 15 for Internet search. 90 % coverage required 11 classes for enterprise and 44 classes for the Internet.

These findings appear to support existing literature in that they show a preference for enterprise searches for specific information using domain specific terms. This paper concludes by considering the implications of these findings for enterprise search systems and PLM in the context of a large engineering organization and in particular proposes two areas of future research.


Knowledge management Enterprise search 



This research is funded via an EPSRC CASE AWARD, the Language of Collaborative Manufacturing (LOCM) Project (EPSRC grant reference EP/K014196/1) and the Airbus Group. The Authors would like to thank colleagues at Airbus and the University of Bristol for support and contribution.


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Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  • David Edward Jones
    • 1
    Email author
  • Yifan Xie
    • 2
  • Chris McMahon
    • 1
  • Marting Dotter
    • 2
  • Nicolas Chanchevrier
    • 2
  • Ben Hicks
    • 1
  1. 1.Department of Mechanical EngineeringUniversity of BristolBristolUK
  2. 2.Airbus GroupToulouseFrance

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