Improving engineering information retrieval by combining TD-IDF and product structure classification
Editor: Anja Maier, Stanko Škec, Harrison Kim, Michael Kokkolaras, Josef Oehmen, Georges Fadel, Filippo Salustri, Mike Van der Loos
Author: Jones, David; Matthews, Jason; Xie, Yifan; Gopsill, James; Dotter, Martin; Chanchevrier, Nicolas; Hicks, Ben
Institution: 1: University of Bristol, United Kingdom; 2: University of the West of England, United Kingdom; 3: Airbus Group, United Kingdom
Section: Design Information and Knowledge
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.