Identifying and tracking scientific and technological knowledge memes from citation networks of publications and patents

Knowledge memes are the cultural equivalent of genes that play an important role in the evolution of knowledge. In this paper, we are trying to identify and tracking scientific and technological knowledge memes, and infer the relationship between science and technology at micro-level. A new carbon nanomaterial—graphene is taken as an example, and publications and patents are used as data sources for the representation of science and technology. Citation networks of publications and patents are constructed, on which a knowledge meme discovery algorithm is used, in order to identify memes that play a key role in the evolution of scientific and technological knowledge. Then the diffusion and co-occurrence of knowledge memes are shown, and a word embedding model is used to track the semantic change of the memes. The research could provide guidance for promoting knowledge innovation and making research policy.     

Measuring international knowledge flows and scholarly impact of scientific research

We introduce a new quantitative measure of international scholarly impact of countries by using bibliometric techniques based on publication and citation data. We present a case study to illustrate the use of our proposed measure in the subject area Energy during 1996–2009. We also present geographical maps to visualize knowledge flows among countries. Finally, using correlation analysis between publication output and international scholarly impact, we study the explanatory power of the applied measure.     

Pattern and trend of scientific knowledge production in North Korea by a semantic network analysis of papers in journal titled technological innovation

Scientometrics - This study aims to examine current trends and patterns of North Korea’s knowledge production in science and technology (S&T) by employing scientometrics analysis. In...     

Measuring knowledge flows between countries: The use of scientific meeting data

The present paper tries to compare international flows of knowledge as measured in meetings with flows as measured with papers in order to see what meetings can add to bibliometric studies. It is shown that most of known bibliometric results are confirmed with meetings, although more skewly: the concentration of proceedings, the dominance and attraction of the United States, and the decline of United Kingdom. However, important limitations are associated with ISTP, namely the low rate of authors' addresses, a limitation which reduces the interest of ISTP for bibliometric studies. Presented at the Sixth International Conference on Scientometrics and Informetrics, Hebrew University, Jerusalem, 16–19 June 1997.     

Analyzing the time delay between scientific research and technology patents based on the citation distribution model

Promoting knowledge diffusion and reducing the delay between scientific research and technology patents is important to achieve success in the highly competitive global environment. This paper studies the time delay between scientific research and technology patents, and focuses on the key components of time in the promotion of knowledge transformation. Based on United States Patent and Trademark Office patent data, we apply periodical citation distribution models to the patent process. The results show that our transfer function model is better than others, and is suitable for calculating the delay between basic scientific research activities and technology patents.     

The utility of scientific papers

This article investigates the function of scientific papers in the production of scientific knowledge. For this production, the citations made of these papers in the scientific literature can be considered as economic utilities. The work of the scientist is described as the production of citations by means of citations. The number of citations received by a given paper can be used to measure the paper's formal utility. The formal utility of scientific papers is studied empirically. It is concluded that the references contained in a scientific paper are a major determinant of its future utility.     

Text representation model of scientific papers based on fusing multi-viewpoint information and its quality assessment

Scientometrics - Text representation is the preliminary work for in-depth analysis and mining of information in scientific papers. It directly affects the effects of downstream tasks such as,...     

Examining patterns of scientific knowledge diffusion based on knowledge cyber infrastructure: a multi-dimensional network approach

Scientometrics - Diffusion of scientific knowledge plays an important role in scientific development. Based on electronic traces of knowledge flows in knowledge cyber infrastructure, this study...     

Identification of technological knowledge intermediaries

Intermediaries in a technological knowledge network have recently been highlighted as crucial innovation drivers that accelerate technological knowledge flows. Although the patent network analysis has been frequently used to monitor technological knowledge structures, it has examined only sources or recipients of the technological knowledge by mainly estimating technological knowledge inflows or outflows of a network node. This study, therefore, aims to identify technological knowledge intermediaries when a technology-level knowledge network is composed of several industries. First, types of technological knowledge flows are deductively classified into four types by highlighting industry affiliations of source technologies and recipient technologies. Second, a directed technological knowledge network is generated at the technology class level, using patent co-classification analysis. Third, for each class, mediating scores are measured according to the four types. The empirical analysis illustrates the Korea’s technological knowledge network between 2000 and 2008. As a result, the four types of mediating scores are compared between industries, and industry-wise technological knowledge intermediaries are identified. The proposed approach is practical to explore converging processes in technology development where technology classes act as technological knowledge intermediaries among diverse industries.     

立足科技创新 光大防伪印刷

目前,中国印刷企业数以万计,特种防伪印刷厂也是多如牛毛,如何在激烈的竞争中立足并且不断发展壮大,创出自己鲜明的特点,是所有印刷人所追求的目标。北京宝旺印务有限公司董事长陈定旺先生引领公司十年发展之路,对探索企业的成功之道很有帮助。靠勤奋与实干成大业陈定旺先生曾是一个背包闯关东的印刷厂业务员。2000年,他在北京     

Visualization of patents and papers in terahertz technology: a comparative study

Terahertz technology is one of the most promising research areas in the 21st century. In this work, we intend to compare the research status quo on terahertz technology between 1990 and 2010 using knowledge domain visualization techniques. Our data consists of 633 patents retrieved from Aureka management platform and 10,344 journal articles indexed in the ISI web of knowledge. Our analysis is a combination of two information visualization tools for analysis, Aureka and CiteSpace. Aureka is allowed for the analysis of patents filed/granted each year, priority country, inventors, assignees, citation counting, and cluster analysis, while networks of co-authors, countries, institutions, document co-citation networks and document co-citation clusters, are performed by CiteSpace. This research provides a comprehensive domain visualization map of innovation and knowledge in the area of terahertz technology. Our result shows that Aureka and CiteSpace are two promising visualization approaches to analyze patents and papers in any given field.     

Beyond patent analytics: Insights from a scientific and technological data mashup based on a case example

Although access to open and commercial digital sources is easily available thanks to the proliferation of the internet, R&D departments still face the challenge of how to analyze information from several sources. This paper addresses this issue specifically when technological and scientific information needs to be analyzed in an integrated manner. 12,577 families of patents, 2601 scientific papers and 706 news articles are combined, normalized and analyzed using their own metadata and text. A software tool is used to extract insights from semi-structured and unstructured data by means of text mining. Additionally, interactive force-directed graph visualization is employed to show the multiple relations of concepts during different time periods with regard to the entire technology ecosystem. Through a case study of 3D printing technology, this paper shows how to apply mashup and obtain the benefits, and it defines the challenges of using interactive visualization representation.     

Indicators for measuring the impact of scientific citations in patents

Scientific publications cited in patents are fundamental elements to assess the transfer of science to technology. Numerous studies evaluate the impact of references in patents and scientific publications and various measurement methods and indicators are proposed. This article reviewed the existing literature on the indicators used to date to determine their suitability and effectiveness to evaluate the impact of patent citations. For this purpose, we analyzed the characteristics of the studies examined and proposed a qualitative classification of indicators from both a technological (patents) and scientific-academic (scientific articles) perspective. Among the results we find that the use of scientometric indicators is primarily focused on analyzing their relevance for patents through the inclusion of scientific citations. Conversely, the same is not true from the academic point of view where gaps still persist in terms of what the impact is when scientific articles are cited in patents. Among the key conclusions is the diversity of proposals to measure scientific citations in patents, though these are conditioned on bibliographic standardization and metadata management of the patents themselves, making it possible to quantify aspects similar to the immediacy index, impact index, or h-index for authors/inventors, albeit from a technological dimension.     

Linkage between patents and papers: An interim EPO/US comparison

A unification of more than one million non-patent references (NPR's) on the front pages of U.S. and EPO patents has been carried out, with a subsequent match to theScience Citation Index (SCI), in order to investigate the citation linkage between patented technology and the scientific research literature. The U.S. system shows an extremely rapid increase in linkage, with citations from U.S. patents to U.S. authored papers increasing more than three-fold over the last decade. The EPO system does not show any increase; the occurrence of non-patent references appears to be relatively constant in the EPO system over the last decade. In the U.S. system approximately 75 percent of the cited papers originate in public science institutions, showing large dependence of patented industrial technology on public science. We expect to find similar result in the EPO system.     

The measurement of a country's scientific and technological potential

The paper suggests a formula for the measurement of the national science and technology potential. This is based on a decision-making framework for the development of indicators for theS & T system.     

Knowledge begets knowledge: university knowledge spillovers and the output of scientific papers from U.S. Small Business Innovation Research (SBIR) projects

Scientometrics - Scientific papers submitted for publication from U.S. Small Business Innovation Research (SBIR)-funded research projects are an innovative output that has yet to be studied...     

Study on the destination of research via knowledge flows

Today, governments tackle the science of science policy with quantitative analysis, especially in the USA. This trend promotes the use of objective data by decision-makers in the fields of innovation policy and technology management. These decision-makers seek more reliable research and development at an earlier stage to contribute to the national economy. Under this worldwide trend, there is a high demand for quantitative analysis accompanying complex IT skills from governmental officers and non-IT researchers. The purpose of this research is to extract the destinations of currently growing fields of science by means of tracking citations and to capture signs of state of the art studies. The analysis data are bibliographic data of academic papers retrieved from Web of Science. I provide results for 16 growing topics as of July 2016. I deepen the understanding of the “convolutional neural network” among a lot of topics, and found future application candidates. I provide a methodology to discover future seeds of research and development. Additionally, the analysis system used in this research automatically publishes its results, and always provides the results. This research will contribute to improving strategies around research and development.     

The influence of disruption on evaluating the scientific significance of papers

Scientometrics - With the exponential growth of the volume of scientific literatures, academic evaluation is becoming one of the important problems of scientometrics. Considering the influence of...     

Modeling the coevolution between citations and coauthorship of scientific papers

Scientometrics - Collaborations and citations within scientific research grow simultaneously and interact dynamically. Modelling the coevolution between them helps to study many phenomena that can...