Discovering and assessing fields of expertise in nanomedicine: a patent co-citation network perspective

Discovering and assessing fields of expertise in emerging technologies from patent data is not straightforward. First, patent classification in an emerging technology being far from complete, the definitions of the various applications of its inventions are embedded within communities of practice. Because patents must contain full record of prior art, co-citation networks can, in theory, be used to identify and delineate the inventive effort of these communities of practice. However, the use patent citations for the purpose of measuring technological relatedness is not obvious because they can be added by examiners. Second, the assessment of the development stage of emerging industries has been mostly done through simple patent counts. Because patents are not all valuable, a better way of evaluating an industry’s stage of development would be to use multiple patent quality metrics as well as economic activity agglomeration indicators. The purpose of this article is to validate the use of (1) patent citations as indicators of technological relatedness, and (2) multiple indicators for assessing an industry’s development stage. Greedy modularity optimization of the ‘Canadian-made’ nanotechnology patent co-citation network shows that patent citations can effectively be used as indicators of technological relatedness. Furthermore, the use of multiple patent quality and economic agglomeration indicators offers better assessment and forecasting potential than simple patent counts.     

Journal co-citation analysis of semiconductor literature

The purpose of this study is to map semiconductor literature using journal co-citation analysis. The journal sample was gathered from the INSPEC database from 1978 to 1997. In the co-citation analysis, the data compiled were counts of the number of times two journal titles were jointly cited in later publications. It is assumed that the more two journals are cited together, the closer the relationship between them. The journal set used was the 30 most productive journals in the field of semiconductors. Counts of co-citations to the set of semiconductor journals were retrieved from SciSearch database, accessed through Dialog. Cluster analysis and multi-dimensional scaling were employed to create two-dimensional maps of journal relationships in the cross-citation networks. The following results were obtained through this co-citation study: The 30 journals fall fairly clearly into three clusters. The major cluster of journals, containing 17 titles, is in the subject of physics. The second cluster, consisting of 9 journals, includes journals primarily on material science. The remaining cluster represents research areas in the discipline of electrical and electronic engineering. All co-cited journals share similar co-citation profiles, reflected in high positive Pearson correlation. Two hundred and ninety-six pairs (68%) correlate at greater than 0.70. This shows that there is strong relationship between semiconductor journals. Five individual journals in five paired sets with co-citation frequency over 100,000 times include Physical Review B, Condensed Matter; Physical Review Letters; Applied Physics Letters; Journal of Applied Physics; and Solid State Communications. This revised version was published online in August 2006 with corrections to the Cover Date.     

Co-citation,bibliographic coupling and a characterization of lattice citation networks

In this article we study directed, acyclic graphs. We introduce the head and tail order relations and study some of their properties. Recalling the notions of generalized bibliographic coupling and generalized co-citation, and introducing a new property, called the l - property, we come to a characterization of lattices. As document citation networks are concrete realizations of directed acyclic graphs all our results are directly applicable to citation analysis. This revised version was published online in June 2006 with corrections to the Cover Date.     

Hybrid documents co-citation analysis: making sense of the interaction between science and technology in technology diffusion

The paper presents a methodology called hybrid documents co-citation analysis, for studying the interaction between science and technology in technology diffusion. Our approach rests mostly on patent citation, cluster analysis and network analysis. More specifically, with the patents citing Smalley RE in Derwent innovations index as the data sets, the paper implemented hybrid documents co-citation network through two procedures. Then spectrum cluster algorithm was used to reveal the knowledge structure in technology diffusion. After that, with the concordance between network properties and technology diffusion mechanisms, three indicators containing degree, betweenness and citation half-life, were calculated to discuss the basic documents in the pivotal position during the technology diffusion. At last, the paper summarized the hybrid documents co-citation analysis in practise, thus concluded that science and technology undertook different functions and acted dominatingly in the different period of technology diffusion, though they were co-activity all the time.     

A Systemic Approach to Exploring an Essential Patent Linking Standard and Patent Maps: Application of Generative Topographic Mapping (GTM)

Abstract:

As the intense competition for the international standardization of technology has increased, many companies are concentrating their capabilities on securing essential patents that claim one or more inventions required to practice a given industry standard; however, despite the importance of developing essential patents, the approaches to exploring promising essential patent: have some limitations in terms of methodology and data. As a remedy, this article proposes a method that derives an essential patent through Generative Topographic Mapping (GTM)-based standard and patent maps. The suggested approach involves a systematic process that identifies vacuums on a standard map in a specific technology field and enables analysts to find candidate for promising essential patents instead of relying on the experts. By applying the proposed methodology, this research discovered the vacuums in an industrial standard document about fuel cell technology as well as the candidates of essential patents in this technology field.     

Benchmarking R&D and companies through patent analysis using free databases and special software: a tool to improve innovative thinking

The availability of free patent databases on the Internet, offers the opportunity of opening the door of patent information not only to patent specialists, but also to many other groups, such as researchers, decision makers, potential inventors and students. The goal of this paper is to show how the combination of free patent databases (in this paper esp@cenet^®) and dedicated software makes it possible to perform easily and rapidly tests on new ideas, the automatic benchmarking of an enterprise's activity and the stimulation of innovative thinking. The benchmarking of companies alone, or of clusters of enterprises is exemplified with reference to the concept of high temperature lubricating oil technology. How to improve innovative thinking is shown within the context of an analysis of coconut technology in postgraduate courses of competitive intelligence provided in Indonesia. Both applications emphasize that the role of patent information is expanding as a unique source of technical information because free availability combined with easy patent mapping and analysis allow non-specialists to use this information source in all technical aspects of innovation, research and development, and strategic planning.     

A dense network sub-grouping algorithm for co-citation analysis and its implementation in the software tool Sitkis

Summary Clustering algorithms are used prominently in co-citation analysis by analysts aiming to reveal research streams within a field. However, clustering of widely cited articles is not robust to small variations in citation patterns. We propose an alternative algorithm, dense network sub-grouping, which identifies dense groups of co-cited references. We demonstrate the algorithm using a data set from the field of family business research and compare it to two alternative methods, multidimensional scaling and clustering. We also introduce a free software tool, Sitkis, that implements the algorithm and other common bibliometric methods. The software identifies journal-, country- and university-specific citation patterns and co-citation groups, enabling the identification of “invisible colleges.”     

Citation networks in information science

The method of co-citation analysis is used to build citation networks in information science. As data base the first 13 volumes (1961–1973) of the leading Soviet journal in the field (Nauchno-tekhnicheskaya Informatsiya) were used. The results reveal the topical structure of information science, the communities of authors and the names of single leading scientists. The evaluation of scientists' work is based on two measures: productivity (with or without co-authorship) and popularity (popularity of authors and popularity of papers).     

Patenting trends in biometric technology of the Big Five patent offices

We examined the overall trends in biometric technology based on patent documents. Using PATSTAT database, we extracted 37,462 patent documents applied at the Big Five patent offices between 1990 and 2016. Latent Dirichlet allocation was applied to their abstracts to observe annual trends by topic. Our results are as follows: Fingerprint-enabled car anti-theft systems have been undergoing rapid technological development since 2014. In response, biometric signal transmitting models are becoming popular owing to concerns about theft of biometric templates. While fingerprint, face, and iris authentication technologies continue to advance, finger vein, voice, and signature authentication technologies are lagging. Use of biometric technologies in financial transactions, server networks, and digital media content security are decreasing as well. A citation analysis discovered key topics and patent applicants: Surprisingly, the quantitative growth rate of topics and the effect on the knowledge network showed an inverse relationship. US firms had the most citations, but fewer backward citations of own work, unlike Japanese companies. We provide practical insights to stakeholders of biometric technology.     

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.     

A comparison of two bibliometric methods for mapping of the research front

Summary This paper builds on previous research concerned with the classification and specialty mapping of research fields. Two methods are put to test in order to decide if significant differences as to mapping results of the research front of a science field occur when compared. The first method was based on document co-citation analysis where papers citing co-citation clusters were assumed to reflect the research front. The second method was bibliographic coupling where likewise citing papers were assumed to reflect the research front. The application of these methods resulted in two different types of aggregations of papers: (1) groups of papers citing clusters of co-cited works and (2) clusters of bibliographically coupled papers. The comparision of the two methods as to mapping results was pursued by matching word profiles of groups of papers citing a particular co-citation cluster with word profiles of clusters of bibliographically coupled papers. Findings suggested that the research front was portrayed in two considerably different ways by the methods applied. It was concluded that the results in this study would support a further comparative study of these methods on a more detailed and qualitative ground. The original data set encompassed 73,379 articles from the fifty most cited environmental science journals listed in Journal Citation Report, science edition downloaded from the Science Citation Index on CD-ROM.     

The evidence of systematic noise in non-patent references: A study of New Zealand companies’ patents

Since the pioneering studies of Carpenter & Narin (1983), and Narin & Noma (1985), non-patent references (NPRs) in patent documents have been widely used as an indicator of science-technology links. Meyer (2000) reviewed previous work in the patent citation literature and found that citation links between patents and papers are, if not explicitly, at least implicitly viewed as an indication of the contribution of science to technology. Using a sample of 850 patents of New Zealand companies granted by the USPTO between 1976 and 2004, we find evidence of systematic noise in NPR data. We suggest that future research should pay close attention to heterogeneity among countries, and that one should demonstrate more caution in applying and interpreting results based on the NPR methodology.     

卷烟包装技术专利分析与研究

目的分析近10年国内外烟草企业包装技术专利的申请情况和专利特点。方法通过对佰腾网、国家知识产权局网等中外专利数据库网站检索到的烟草企业在2004年至2013年间的包装技术类专利进行统计,并采用对比分析法等方法分析国内外大型烟企在包装领域专利申请情况、技术分布及研发趋势。结论烟草企业的包装领域已逐渐成为国内外包装科技创新的主力,发明专利是国外烟草企业专利的主要形式,国内烟草企业发明专利申请所占比重较低,专利结构有待优化。国内外烟草企业申请最多的包装技术专利为包装盒形、烟用滤棒和卷烟纸技术等内容。     

The Patent Documentation Group (PDG)

The PDG was founded in 1957 by thirteen European chemical and oil companies, with the main aim of abstracting patent documents and searching for patent families. During the 1960s the group became engaged in other activities, notably exchanging views on patent information management matters and testing new systems for polymer patents.In 1969 the Group was reorganised with a permanent secretary in Basel, and objectives and activities fixed by statutes. In the early 1970s, due to the development of Derwent's abstract services, the PDG discontinued its abstracting work, and efforts were concentrated on Working Groups studying matters such as networks and online retrieval, microfilm equipment, and developments in national and international patent laws. In 1984 the statutes were changed to allow ‘non-chemical’ companies to become members, and in 1985 membership increased to 23 companies covering five countries.     

Identification and evaluation of corporations for merger and acquisition strategies using patent information and text mining

This paper proposes a framework to identify and evaluate companies from the technological perspective to support merger and acquisition (M&A) target selection decision-making. This employed a text mining-based patent map approach to identify companies which can fulfill a specific strategic purpose of M&A for enhancing technological capabilities. The patent map is the visualized technological landscape of a technology industry by using technological proximities among patents, so companies which closely related to the strategic purpose can be identified. To evaluate the technological aspects of the identified companies, we provide the patent indexes that evaluate both current and future technological capabilities and potential technology synergies between acquiring and acquired companies. Furthermore, because the proposed method evaluates potential targets from the overall corporate perspective and the specific strategic perspectives simultaneously, more robust and meaningful result can be obtained than when only one perspective is considered. Thus, the proposed framework can suggest the appropriate target companies that fulfill the strategic purpose of M&A for enhancing technological capabilities. For the verification of the framework, we provide an empirical study using patent data related to flexible display technology.     

Knowledge-transfer analysis based on co-citation clustering

Based on co-citation cluster analysis, we propose a knowledge-transfer analysis model for any technology field. In this model, patent data with backward citations to non-patent literature and forward citations by later patents would be analyzed. Co-citation clustering of the cited articles defines scientific knowledge sources, while that of the patents themselves defines technology fronts. According to the citation between the article and patent clusters, the landscape of knowledge-transfer including route and strength between scientific knowledge sources and technology fronts can be mapped out. The model has been applied to the field of transgenic rice. As a result of the analysis, ten scientific knowledge sources and eight technology fronts have emerged, and reasonable links between them have been established, which clearly show how knowledge has been transferred in this field.     

The interdisciplinary structure of research on intercultural relations: a co-citation network analysis study

This study aims to map the content and structure of the knowledge base of research on intercultural relations as revealed in co-citation networks of 30 years of scholarly publications. Source records for extracting co-citation information are retrieved from Web of Science (1980–2010) through comprehensive keyword search and filtered by manual semantic coding. Exploratory network and content analysis is conducted (1) to discover the development of major research themes and the relations between them over time; (2) to locate representative core publications (the stars) that are highly co-cited with others and those (the bridges) connecting more between rather than within subfields or disciplines. Structural analysis of the co-citation networks identifies a core cluster that contains foundational knowledge of this domain. It is well connected to almost all the other clusters and covers a wide range of subject categories. The evolutionary path of research themes shows trends moving towards (e.g. psychology and business and economics) and away from (e.g. language education and communication) the core cluster over time. Based on the results, a structural framework of the knowledge domain of intercultural relations research is proposed to represent thematic relatedness between topical groups and their relations.     

Using patent analysis to explore corporate growth

This study applies patent analysis to discuss the influences of the three aspects of patent trait—a firm’s revealed technology advantage in its most important technological field (RTA_MIT), relative patent position in its most important technological field (RPP_MIT), and patent share in its most important technological field (PS_MIT)—upon corporate growth and discusses the moderation effect of relative growth rate of its most important technological field (RGR_MIT) in the American pharmaceutical industry. The results demonstrate that the three relationships between corporate growth and the three aspects of patent trait are positive, and verify that RGR_MIT moderates the three relationships. This study suggests that pharmaceutical companies should enhance their R&D capabilities, the degree of leading position, and concentration of R&D investment in their most important technological fields to increase their growth. Finally, this study classifies the pharmaceutical companies into four types, and provides some suggestions to them.     

A new instrument for technology monitoring: novelty in patents measured by semantic patent analysis

Given that in terms of technology novel inventions are crucial factors for companies; this article contributes to the identification of inventions of high novelty in patent data. As companies are confronted with an information overflow, and having patents reviewed by experts is a time-consuming task, we introduce a new approach to the identification of inventions of high novelty: a specific form of semantic patent analysis. Subsequent to the introduction of the concept of novelty in patents, the classical method of semantic patent analysis will be adapted to support novelty measurement. By means of a case study from the automotive industry, we corroborate that semantic patent analysis is able to outperform available methods for the identification of inventions of high novelty. Accordingly, semantic patent information possesses the potential to enhance technology monitoring while reducing both costs and uncertainty in the identification of inventions of high novelty.