Improving engineering information retrieval by combining TD-IDF and product structure classification

D. Jones, Jason Matthews, Yifan Xie, James Gopsill, Martin Dotter, Nicolas Chanchevrier, Ben Hicks

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

3 Citations (SciVal)

Abstract

Engineering Information Management (EIM) and Information Retrieval (IR) systems are central to the day to day running of large engineering organisations. The capture, interrogation, retrieval and presentation of information from design to disposal is considered to be a key enabler for greater efficiency and decision making and in turn improved productivity, profitability and competitiveness. This paper presents a contribution to the field of engineering IR through combining TF-IDF with classification against the product structure. The results of this initial investigation show that Precision, Recall and F1-Scores can be improved depending on the method of results integration and thus tailored to the search system and context.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Engineering Design, ICED
EditorsF. Salustri, S. Skec, A. M. Maier, H. Kim, M. Kokkolaras, J. Oehmen, G. Fadel, M. Van der Loos
PublisherElsevier
Pages41-50
Number of pages10
Volume6
EditionDS87-6
Publication statusPublished - 2017

Publication series

NameProceedings of the International Conference on Engineering Design, ICED
ISSN (Print)2220-4334

Keywords

  • Design informatics
  • Information management
  • Knowledge management
  • Product Lifecycle Management (PLM)

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