1,721,128 research outputs found
Dalla metrica dei consumi alle capabilities: un analisi multidimensionale della povertà in Puglia
No full textA simple and fast method for Named Entity context extraction from patents
No full textThe process of extracting relevant technical information from patents or technical literature is as valuable as it is challenging. It deals with highly relevant information extraction from a corpus of documents with particular structure, and a mix of technical and legal jargon. Patents are the wider free source of technical information where homogeneous entities can be found. From a technical perspective the approaches refer to Named Entity Recognition (NER) and make use of Machine Learning techniques for Natural Language Processing (NLP). However, due to the large amount of data, to the complexity of the lexicon, the peculiarity of the structure and the scarcity of the examples to be used to feed the machine learning system, new approaches should be studied. NER methods are increasing their performances in many contexts, but a gap still exists when dealing with technical documentation. The aim of this work is to create an automatic training sets for NER systems by exploiting the nature and structure of patents, an open and massive source of technical documentation. In particular, we focus on collecting the context where users of the invention appear within patents. We then measure to which extent we achieve our goal and discuss how much our method is generalizable to other entities and documents
A DATA DRIVEN TOOL TO SUPPORT DESIGN TEAM COMPOSITION MEASURING SKILLS DIVERSITY
No full textTeam 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
Impact for whom? Mapping the users of public research with lexicon-based text mining
No full textWe contribute to the debate on societal impact of SSH by developing a methodology that allows a fine-grained observation of social groups that make use, directly or indirectly, of the results of research. We develop a lexicon of users with 76,857 entries, which saturates the semantic field of social groups of users and allows normalization. We use the lexicon in order to filter text structures in the 6637 impact case studies collected under the Research Excellence Framework in the UK. We then follow the steps recommended by Börner et al. (Annu Rev Inf Sci Technol 37:179–255, 2003) to build up visual maps of science, using co-occurrence of words describing users of research. We explore the properties of this novel kind of maps, in which science is seen from the perspective of research users
Le trasformazioni di una città del sud: Molfetta
No full textLa città di Molfetta sita nell'area metropolitana di Bari viene guardata da un economista, un sociologo ed un urbanista attraverso visioni retrospettive e sul futuro delle risorse territoriali economiche e sociali di una città che attraversa la nuova stagione della riforma dell'elezione dei sindaci
Technical Sentiment Analysis. Measuring Advantages and Drawbacks of New Products Using Social Media
No full textThe paper contributes to the literature on sentiment analysis by introducing a new knowledge-based lexicon. The lexicon, based on fundamental research and systematic practice in Engineering Design, describes the Advantages or Drawbacks (Disadvantages) of products as an effect of the interaction between artifacts and users. The paper extracts data from Twitter that report consumer conversations after the launch of new products in the videogame industry. It compares the results of a traditional sentiment analysis with the results filtered using the lexicon. We observe a drop in the number of positive tweets but a sharp increase in the informativeness of consumers’ opinions. Comments filtered using the lexicon offer a much more useful basis for understanding customers and designing new products. The paper develops several areas of potential applicability of the methodology
Data science for engineering design: State of the art and future directions
Full text linkEngineering design (ED) is the process of solving technical problems within requirements and constraints to create new artifacts. Data science (DS) is the inter-disciplinary field that uses computational systems to extract knowledge from structured and unstructured data. The synergies between these two fields have a long story and throughout the past decades, ED has increasingly benefited from an integration with DS. We present a literature review at the intersection between ED and DS, identifying the tools, algorithms and data sources that show the most potential in contributing to ED, and identifying a set of challenges that future data scientists and designers should tackle, to maximize the potential of DS in supporting effective and efficient designs. A rigorous scoping review approach has been supported by Natural Language Processing techniques, in order to offer a review of research across two fuzzy-confining disciplines. The paper identifies challenges related to the two fields of research and to their interfaces. The main gaps in the literature revolve around the adaptation of computational techniques to be applied in the peculiar context of design, the identification of data sources to boost design research and a proper featurization of this data. The challenges have been classified considering their impacts on ED phases and applicability of DS methods, giving a map for future research across the fields. The scoping review shows that to fully take advantage of DS tools there must be an increase in the collaboration between design practitioners and researchers in order to open new data driven opportunities
High-order Finite Volume WENO schemes for non-local multi-class traffic flow models
No full textThis paper focuses on the numerical approximation of a class of non-local systems of conservation laws in one space dimension, arising in traffic modeling, proposed by [F. A. Chiarello and P. Goatin. Non-local multi-class traffic flow models. Networks and Heteroge-neous Media, to appear, Aug. 2018]. We present the multi-class version of the Finite Volume WENO (FV-WENO) schemes [C. Chalons, P. Goatin, and L. M. Villada. High-order numerical schemes for one-dimensional non-local conservation laws. SIAM Journal on Scientific Computing, 40(1):A288–A305, 2018.], with quadratic polynomial reconstruction in each cell to evaluate the non-local terms in order to obtain high-order of accuracy. Simulations using FV-WENO schemes for a multi-class model for autonomous
and human-driven traffic flow are presented for M =
Twenty years of gender equality research: A scoping review based on a new semantic indicator
Full text linkGender equality is a major problem that places women at a disadvantage thereby stymieing economic growth and societal advancement. In the last two decades, extensive research has been conducted on gender related issues, studying both their antecedents and consequences. However, existing literature reviews fail to provide a comprehensive and clear picture of what has been studied so far, which could guide scholars in their future research. Our paper offers a scoping review of a large portion of the research that has been published over the last 22 years, on gender equality and related issues, with a specific focus on business and economics studies. Combining innovative methods drawn from both network analysis and text mining, we provide a synthesis of 15,465 scientific articles. We identify 27 main research topics, we measure their relevance from a semantic point of view and the relationships among them, highlighting the importance of each topic in the overall gender discourse. We find that prominent research topics mostly relate to women in the workforce-e.g., concerning compensation, role, education, decision-making and career progression. However, some of them are losing momentum, and some other research trends-for example related to female entrepreneurship, leadership and participation in the board of directors-are on the rise. Besides introducing a novel methodology to review broad literature streams, our paper offers a map of the main gender-research trends and presents the most popular and the emerging themes, as well as their intersections, outlining important avenues for future research
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