Problems: easy to say but difficult to write

DS 122: Proceedings of the Design Society: 24th International Conference on Engineering Design (ICED23)

Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nad
Author: Giordano, Vito (1,3); Consoloni, Marco (1,3); Chiarello, Filippo (1,3); Fantoni, Gualtiero (2,3)
Series: ICED
Institution: 1: School of Engineering, Department of Energy, Systems, Land and Construction Engineering, University of Pisa, Italy; 2: School of Engineering, Department of Civil and Industrial Engineering, University of Pisa, Italy;; 3: B4DS - Business Engineering for Data Science lab, University of Pisa, Italy
Section: Design Methods
Page(s): 2945-2954
DOI number:


Patents are an invaluable source of data that can be beneficial for Engineering Design (ED). Patenting is one of the main means for disclosing the inventive process. For this reason, the description of the problem solved should also be included in any patents.

The ED literature lacks a proper definition of a problem, resulting in a fragmented scenario. Prior studies have employed Text Mining (TM) to extract problems from patents. We argue that TM can assist ED researchers in understanding how problems are articulated in text. Based on the literature, we propose two hypotheses: (1) problem-related text exhibits a negative sentiment polarity compared to other sections of patents; (2) problem-related keywords identified in the literature are predominantly used to describe problems rather than other aspects.

We analyse Japanese patents to validate our hypotheses, since they explicit Problem and Solution in the abstract. Finally, we compare our results with a set of problem-related sentences extracted from USPTO patents.

Our study reveals a higher positive sentiment in problem-related sentences compared to solution-related ones and highlights the inadequacy of using problem-related keywords alone to differentiate between the two.

Keywords: Patent Analysis, Text mining, Knowledge management, Semantic data processing, Conceptual design

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