Author: VPInstitute
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Application of Text-Analytics in Quantitative Study of Science and Technology
The quantitative study of science, technology and innovation (ST&I ) has experienced significant growth with advancements in disciplines such as mathematics, computer science and information sciences. From the early studies utilizing the statistics method, graph theory, to citations or co-authorship, the state of the art in quantitative methods leverages natural language processing and machine learning.…
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TECHNOLOGICAL INNOVATIONS OF THE 3D PRINTER APPLIED TO HEALTH (INOVAÇÕES TECNOLÓGICAS DA IMPRESSORA 3D APLICADA À SAÚDE) FULL-TEXT
3D printing technology has already been created by the manufacturing industry for decades. In the health area has grown rapidly, allowing the application to various areas of medicine. This work carried out a quantitative study in patent databases with the aim of sticking to the innovations that emerged with the 3D printer applied to health…
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GLOBAL HIMALAYA PLANT RESEARCH TREND AND PERFORMANCE IN SCIENCE CITATION INDEX FROM 1998 TO 2017 (FULL-TEXT)
Himalaya plants have essential ecological implications and are frequently used by local tribes for various purposes, many of which are traditionally used to cure various ailments in humans and livestock. In this study, we aimed to evaluate the global scientific production of Himalaya plant research, study the characteristics of Himalaya plant research activities, and identify…
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Fine-grained Construction of Semantic Technology Network for Technology Evolution Analysis
As a basic tool for technology evolution analysis, technology network can visualize the relationship among technologies in different patents. However, the current constructions of technology network only represent common technical information, and cannot reflect different types of technical information. We propose a new approach to construct a fine-grained technology network and display technical information from…
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The role of knowledge intensive business services in economic development: a bibliometric analysis from Bradford, Lotka and Zipf laws (FULL-TEXT)
The international scientific community considers Knowledge Intensive Business Services (KIBS) as one of the main themes related to innovation and economic development. This article presents a review based on Scopus and ISI Web of Knowledge databases, on the KIBS topic in the world, considering the period 2000-2017. The study aimed to understand the role of…
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An integrated solution for detecting rising technology stars in co-inventor networks
Online patent databases are powerful resources for tech mining and social network analysis and, especially, identifying rising technology stars in co-inventor networks. However, it’s difficult to detect them to meet the different needs coming from various demand sides. In this paper, we present an unsupervised solution for identifying rising stars in technological fields by mining…
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A hybrid approach to detecting technological recombination based on text mining and patent network analysis
Detecting promising technology groups for recombination holds the promise of great value for R&D managers and technology policymakers, especially if the technologies in question can be detected before they have been combined. However, predicting the future is always easier said than done. In this regard, Arthur’s theory (The nature of technology: what it is and…
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The Relationship between Forward and Backward Diversity in CORE Datasets
In this paper we seek to better understand the relationship between forward diversity in the Cognitive Science and Educational Research literature, as well as what we call Border fields (i.e. those fields which exist at the intersection of Cognitive Science and Education Research). We find a clear and convincing relationship between forward and backward diversity…
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Learning about learning: patterns of sharing of research knowledge among Education, Border, and Cognitive Science fields
This study explores the patterns of exchange of research knowledge among Education Research, Cognitive Science, and what we call “Border Fields.” We analyze a set of 32,121 articles from 177 selected journals, drawn from five sample years between 1994 and 2014. We profile the references that those articles cite, and the papers that cite them.…
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Does deep learning help topic extraction? A kernel k-means clustering method with word embedding
Topic extraction presents challenges for the bibliometric community, and its performance still depends on human intervention and its practical areas. This paper proposes a novel kernel k-means clustering method incorporated with a word embedding model to create a solution that effectively extracts topics from bibliometric data. The experimental results of a comparison of this method…