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Text and Dynamic Network Analysis for Measuring Technological Convergence: A Case Study on Defense Patent data

IEEE TRANSACTIONS ON engineering MANAGEMENT 2023年第4期70卷 1490-1503页

作者： Giordano, Vito Chiarello, Filippo Melluso, Nicola Fantoni, Gualtiero bonaccorsi, Andrea Univ Pisa Dept Informat Engn I-56120 Pisa Italy Univ Pisa Business Engn Data Sci Lab B4DS I-56120 Pisa Italy Univ Pisa Dept Energy Syst Terr & Construct Engn I-56120 Pisa Italy Univ Pisa Business Engn Data Sci Lab B4DS I-56120 Pisa Italy Erre Quadro SRL I-56126 Pisa Italy Univ Pisa Dept Civil & Ind Engn & I-56120 Pisa Italy

Identifying technology convergence is getting harder, especially in fast-evolving and cross-technological fields. On the other side, natural language processing and network analysis researchers is to provide a novel method for mapping technologies and their relations over time, in order to identify dynamic patterns of convergence and to test it on the C4ISTAR field, a defense-related cross-technological field. The methodology automatically extracts technologies from a corpus of scientific papers, policy documents, websites, and company reports using Named Entity Recognition approaches. These technologies are then retrieved from the second corpus of more than 300 thousand patents related to the C4ISTAR domain, measuring their cooccurrences over time. Finally, using the time-varying network analysis, we were able to identify and measure the pattern of technological convergence.

关键词： Convergence Patents Training Industries Electronic mail Command and control systems business Defense sector natural language processing (NLP) patents analysis technological convergence text mining

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PRObLEMS: EASY TO SAY bUT DIFFICULT TO WRITE 24

PROBLEMS: EASY TO SAY BUT DIFFICULT TO WRITE

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24th International Conference on engineering Design, ICED 2023

作者： Giordano, Vito Consoloni, Marco Chiarello, Filippo Fantoni, Gualtiero School of Engineering Department of Energy Systems Land and Construction Engineering University of Pisa Italy School of Engineering Department of Civil and Industrial Engineering University of Pisa Italy B4DS - Business Engineering for Data Science Lab University of Pisa Italy

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. © The Author(s), 2023. Published by Cambridge University Press.

关键词： Conceptual design

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WHAT USERS WANT: A NATURAL LANGUAGE PROCESSING APPROACH TO DISCOVER USERS' NEEds FROM ONLINE REVIEWS 24

WHAT USERS WANT: A NATURAL LANGUAGE PROCESSING APPROACH TO D...

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24th International Conference on engineering Design, ICED 2023

作者： Spada, Irene barandoni, Simone Giordano, Vito Chiarello, Filippo Fantoni, Gualtiero Martini, Antonella School of Engineering Department of Information Engineering University of Pisa Italy Department of Computer Science University of Pisa Italy School of Engineering Department of Energy Systems Land and Construction Engineering University of Pisa Italy School of Engineering Department of Civil and Industrial Engineering University of Pisa Italy B4DS - Business Engineering for Data Science Lab University of Pisa Italy

Digital media are a means to deliver products and services, but also a channel to interact with consumers and a source of information on users' preferences. data shared by customers on the web, the User-Generated Content (UGC), can give entrepreneurs a detailed perspective of the market. This work examines an application of Natural Language Processing techniques on UGC to discover insights on users' opinions. We collected more than 13.000 reviews of software from digital stores and review website to gather information on the customers' perspective and their response to a given marketing strategy in two case studies on digital product's launch. The objective is to give support to two Italian companies in the process of business model development through data-driven evidence. We aim to discover who are the users and which are their needs using a lexicon-based approach to mine unstructured text. The results provide qualitative and quantitative descriptions of the market segments. We propose a method to examine UGC and to explore customers' behavior on social media. The findings helped managers for the development of their business model, enhancing an informed decision-making process. © The Author(s), 2023. Published by Cambridge University Press.

关键词： Digital storage

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A data DRIVEN TOOL TO SUPPORT DESIGN TEAM COMPOSITION MEASURING SKILLS DIVERSITY 24

A DATA DRIVEN TOOL TO SUPPORT DESIGN TEAM COMPOSITION MEASUR...

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24th International Conference on engineering Design, ICED 2023

作者： Chiarello, Filippo Spada, Irene barandoni, Simone Giordano, Vito Fantoni, Gualtiero School of Engineering Department of Energy Systems Land and Construction Engineering University of Pisa Italy School of Engineering Department of Civil and Industrial Engineering University of Pisa Italy School of Engineering Department of Engineering Informatics University of Pisa Italy Department of Informatics University of Pisa Italy B4DS - Business Engineering for Data Science Lab University of Pisa Italy

Team composition in Project based Learning is the first task for the class and has a great impact on the learning experience. Anyway, little space is dedicated in literature about team composition, considering their personal inclinations towards design tasks. For these reasons we propose a tool that aims to map the design skills of students to optimise team composition. The tool is based on a questionnaire grounded in the design theory and aims at measuring the willingness of students at performing certain design tasks. The results of the questionnaires are analysed using Principal Component Analysis to normalise each students' answers to the whole class, and to show the distribution of students in the space of engineering design skills. We present the design process of the tool, and a first experimentation on two classes of master's degree students in Management engineering and data science, testing the tool on a total of 72 students. The results are promising and demonstrate the robusteness of the questionnaire and of the analytical method. Also, we propose next steps for our research activity, calling for other researchers to test our method in different contexts. © The Author(s), 2023. Published by Cambridge University Press.

关键词： Students

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Detecting bad design and bias from patents 23

Detecting bad design and bias from patents

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23rd International Conference on engineering Design, ICED 2021

作者： Melluso, Nicola Pardelli, Sara Fantoni, Gualtiero Chiarello, Filippo bonaccorsi, Andrea University of Pisa Department of Civil and Industrial Engineering Italy B4DS Lab - Business Engineering for Data Science Erre Quadro s.r.l.

The representation of the product use context is a well established design practice in engineering Design. Recently, design theory is studying the product interaction involving several cognitive aspects such as the possible conditions in which a wrong interaction occurs. The aim of this paper is to find a quantitative evidence of the causes of these misuses. In particular, this study focuses on the detection of bad design and biases. In this paper, we propose a method that helps to the automatic detection of bad design and biases from patents. The method is based on an approach that defines syntactic rules to detect sentences containing these artifacts. These rules are defined based on an exploratory analysis of the explicit mention of "bad design" and "bias" and then, tested with multiple experiments on a sample of patents. The results give a first quantitative evidence of the presence of bad design and biases in patents and consequently of their importance in the design theory. In particular, it is provided a fine grain analysis of the linguistic structure of sentences containing these artifacts helping designers in detecting automatically them from patents. © ICED *** right reserved.

关键词： Semantics

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DETECTING bAD DESIGN AND bIAS FROM PATENTS

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Proceedings of the Design Society 2021年 1卷 1173-1182页

作者： Nicola Melluso Sara Pardelli Gualtiero Fantoni Filippo Chiarello Andrea bonaccorsi University of Pisa B4DS Lab - Business Engineering for Data Science Erre Quadro s.r.l.

The representation of the product use context is a well established design practice in engineering Design. Recently, design theory is studying the product interaction involving several cognitive aspects such as the possible conditions in which a wrong interaction occurs. The aim of this paper is to find a quantitative evidence of the causes of these misuses. In particular, this study focuses on the detection of bad design and *** this paper, we propose a method that helps to the automatic detection of bad design and biases from patents. The method is based on an approach that defines syntactic rules to detect sentences containing these artifacts. These rules are defined based on an exploratory analysis of the explicit mention of “bad design” and “bias” and then, tested with multiple experiments on a sample of patents. The results give a first quantitative evidence of the presence of bad design and biases in patents and consequently of their importance in the design theory. In particular, it is provided a fine grain analysis of the linguistic structure of sentences containing these artifacts helping designers in detecting automatically them from patents.

关键词： Design cognition Design theory Semantic data processing bad Design bias

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data for engineering design: Maps and gaps 23

Data for engineering design: Maps and gaps

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23rd International Conference on engineering Design, ICED 2021

作者： Chiarello, Filippo Coli, Elena Giordano, Vito Fantoni, Gualtiero bonaccorsi, Andrea Department of Energy Systems Territory and Construction Engineering University of Pisa Italy Department of Information Engineering University of Pisa Italy Department of Civil and Industrial Engineering University of Pisa Italy B4DS Lab - Business Engin

data, information and knowledge are strongly involved in engineering Design (ED) process. Despite the crucial role played by data in the design process, there is a lack of studies about how different data are used and generated by the various phases of the ED process. This study is a first attempt to fill this gap by mapping which data types are involved in the different ED phases from a research perspective. In order to achieve this objective, we used a methodology based on Text Mining. Firstly, we retrieve a corpus of scientific papers related to ED;then, we build two lexicons to recognize ED phases and data types;finally, we collect these entities within ED papers and map the relations between them. The methodology application allows the building of a network graph for visualizing the relations among data lexicon and ED lexicon. Then, we investigate the specific relations among data types and ED phases by building a heatmap to investigate data types from 3 different perspective. The insight coming from our analysis shows that ED studies have a great potential in the usage of many data sources, but also that there exist some gaps to be solved in order to reach a more effective data usage in the context of ED. © ICED *** right reserved.

关键词： Knowledge management

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An Open data Repository for engineering Design: Using Text Mining with Open Government data

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COMPUTERS IN INDUSTRY 2022年 142卷

作者： Giordano, Vito Coli, Elena Martini, Antonella Dept Informat Engn Via Girolamo Caruso 16 I-56122 Pisa Italy Dept Energy Syst Terr & Construct Engn Largo Lucio Lazzarino 2 I-56122 Pisa Italy Business Engn Data Sci B4DS Res Lab Pisa Italy

engineering Design (ED) is a complex process in which the reuse of knowledge is crucial: applying the knowledge consolidated in previous design activities to future design activities means performing them in a better way. The relevance of data in ED is even more crucial in a business context in which data science (ds) is literally revolutionizing the way companies operate and therefore also the way data are analyzed. Despite having been recognized as crucial for ED processes, data still remain closed in the domain and accessible only to their owners due to several constraints related to the private and proprietary nature of the acquired data. An answer to these challenges could be found in Open data, but at the state of the art an operational engineering Design framework to embrace them is still far to be achieved by both academia and industry. Given these issues, the aim of this paper is to give evidence that Text Mining can help to make a complex open database more effective to be used for the ED process, taking U.S. Open Government data (OGD) repository as a case study. Open access to methods and data used within this research is provided. The results of this study allow us to understand for which purposes it is possible to apply the datasets and to comprehend the expertise and the data science methods needed for processing different data for-mats. Moreover, this work opens relevant implications and challenges for researchers, practitioners and policy makers operating in ED and ds domains that could become opportunities for future research and industrial applications. (c) 2022 Elsevier b.V. All rights reserved.

关键词： engineering Design Natural Language Processing Open data Open Government data Open data Repository

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data FOR engineering DESIGN: MAPS AND GAPS

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Proceedings of the Design Society 2021年 1卷 821-830页

作者： Filippo Chiarello Elena Coli Vito Giordano Gualtiero Fantoni Andrea bonaccorsi Department of Energy Systems Territory and Construction Engineering University of Pisa B4DS Lab - Business Engin Department of Information Engineering University of Pisa Department of Civil and Industrial Engineering University of Pisa

data, information and knowledge are strongly involved in engineering Design (ED) process. Despite the crucial role played by data in the design process, there is a lack of studies about how different data are used and generated by the various phases of the ED process. This study is a first attempt to fill this gap by mapping which data types are involved in the different ED phases from a research *** order to achieve this objective, we used a methodology based on Text Mining. Firstly, we retrieve a corpus of scientific papers related to ED; then, we build two lexicons to recognize ED phases and data types; finally, we collect these entities within ED papers and map the relations between *** methodology application allows the building of a network graph for visualizing the relations among data lexicon and ED lexicon. Then, we investigate the specific relations among data types and ED phases by building a heatmap to investigate data types from 3 different *** insight coming from our analysis shows that ED studies have a great potential in the usage of many data sources, but also that there exist some gaps to be solved in order to reach a more effective data usage in the context of ED.

关键词： Semantic data processing Knowledge management Information management data Types Text Mining

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Unveiling the Inventive Process from Patents by Extracting Problems, Solutions and Advantages with Natural Language Processing

SSRN

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SSRN 2022年

作者： Giordano, Vito Puccetti, Giovanni Chiarello, Fllippo Pavanello, Tommaso Fantoni, Gualtiero Department of Information Engineering Via Girolamo Caruso 16 Pisa56122 Italy Scuola Normale Superiore Piazza dei Cavalieri 7 Pisa56126 Italy Department of Energy Systems Territory and Construction Engineering Largo Lucio Lazzarino 2 Pisa56122 Italy Erre Quadro S.R.L Largo Padre Renzo Spadoni c/o Cittadella Galileiana Pisa56126 Italy Department of civil and industrial engineering Largo Lucio Lazzarino 2 Pisa56122 Italy Business Engineering for Data Science B4DS Research Laboratory Italy

Patents are the main means for disclosing an invention. These documents encompass many steps of the inventive process starting with the definition of the problem to be solved and ending with the identification of a solution. In this study we focus on three fundamental concepts of the inventive process: (A) technical problems;(b) solutions;and (C) advantageous effects of the invention, which, based on the WIPO guidelines, any patent should *** propose a system based on Natural Language Processing (NLP) pipeline that uses transformer language models to identify technical problems, solutions and advantageous effects from patents. We use a training dataset composed of 480,000 patents sentences contained in sections manually labeled by inventors or *** model reaches a F1 score of 90%. The model is evaluated on a random set of patents to assess its deployability in a real world *** proposed model can be used as a novel tool for prior art mapping, novel ideas generation and technological evolution identification and can help to disclose valuable information hidden in patent documents. © 2022, The Authors. All rights reserved.

关键词： Patents and inventions

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