Search (439 results, page 1 of 22)

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Abstract

Effective patent management is essential for organizations to maintain their competitive advantage. The classification of patents is a critical part of patent management and industrial analysis. This study proposes a hybrid-patent-classification approach that combines a novel patent-network-based classification method with three conventional classification methods to analyze query patents and predict their classes. The novel patent network contains various types of nodes that represent different features extracted from patent documents. The nodes are connected based on the relationship metrics derived from the patent metadata. The proposed classification method predicts a query patent's class by analyzing all reachable nodes in the patent network and calculating their relevance to the query patent. It then classifies the query patent with a modified k-nearest neighbor classifier. To further improve the approach, we combine it with content-based, citation-based, and metadata-based classification methods to develop a hybrid-classification approach. We evaluate the performance of the hybrid approach on a test dataset of patent documents obtained from the U.S. Patent and Trademark Office, and compare its performance with that of the three conventional methods. The results demonstrate that the proposed patent-network-based approach yields more accurate class predictions than the patent network-based approach.

Date

22. 1.2011 13:04:21

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Abstract

Citations from patents to scientific publications provide useful evidence about the commercial impact of academic research, but automatically searchable databases are needed to exploit this connection for large-scale patent citation evaluations. Google covers multiple different international patent office databases but does not index patent citations or allow automatic searches. In response, this article introduces a semiautomatic indirect method via Bing to extract and filter patent citations from Google to academic papers with an overall precision of 98%. The method was evaluated with 322,192 science and engineering Scopus articles from every second year for the period 1996-2012. Although manual Google Patent searches give more results, especially for articles with many patent citations, the difference is not large enough to be a major problem. Within Biomedical Engineering, Biotechnology, and Pharmacology & Pharmaceutics, 7% to 10% of Scopus articles had at least one patent citation but other fields had far fewer, so patent citation analysis is only relevant for a minority of publications. Low but positive correlations between Google Patent citations and Scopus citations across all fields suggest that traditional citation counts cannot substitute for patent citations when evaluating research.

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Abstract

Patent analysis has become important for management as it offers timely and valuable information to evaluate R&D performance and identify the prospects of patents. This study explores the scattering patterns of patent impact based on citations in 3 distinct technological areas, the liquid crystal, semiconductor, and drug technological areas, to identify the core patents in each area. The research follows the approach from Bradford's law, which equally divides total citations into 3 zones. While the result suggests that the scattering of patent citations corresponded with features of Bradford's law, the proportion of patents in the 3 zones did not match the proportion as proposed by the law. As a result, the study shows that the distributions of citations in all 3 areas were more concentrated than what Bradford's law proposed. The Groos (1967) droop was also presented by the scattering of patent citations, and the growth rate of cumulative citation decreased in the third zone.

Date

22. 8.2014 17:11:29

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Abstract

Mittels Patentindikatoren ist es möglich, wesentliche Erfinder und Erfindungen hervorzuheben. Die Anwendbarkeit von Patentindikatoren ist zeitabhängig. Der eingeführte Patentindikator SPI (Science-on-Patent Influence) signalisiert den Grad der Wissenschaftlichkeit des Erfinders und seiner Erfindungen. Seine rarionelle Nutzung zur Ermittlung von Kerninformation wird vorgestellt

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Abstract

Patents sometimes cite webpages either as general background to the problem being addressed or to identify prior publications that limit the scope of the patent granted. Counts of the number of patents citing an organization's website may therefore provide an indicator of its technological capacity or relevance. This article introduces methods to extract URL citations from patents and evaluates the usefulness of counts of patent web citations as a technology indicator. An analysis of patents citing 200 US universities or 177 UK universities found computer science and engineering departments to be frequently cited, as well as research-related webpages, such as Wikipedia, YouTube, or the Internet Archive. Overall, however, patent URL citations seem to be frequent enough to be useful for ranking major US and the top few UK universities if popular hosted subdomains are filtered out, but the hit count estimates on the first search engine results page should not be relied upon for accuracy.

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Abstract

Citation analysis of patents uses bibliometric techniques to analyze the wealth of information contained in patents. Describes the various facets of patent citations and patent citation studies and their important applications. Describes the construction of technology indicators based on patent citation analysis, including: identification of leading edge technological activity; measurement of national patent citation performance; competitive intelligence; linkages to science; measurement of foreign dependence; highly cited patents; and number of non patent links

Source

World patent information. 19(1997) no.4, S.269-272

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Abstract

This study employs a panel threshold regression model to test whether the patent h-index has a threshold effect on the relationship between patent citations and market value in the pharmaceutical industry. It aims to bridge the gap in extant research on this topic. This study demonstrates that the patent h-index has a triple threshold effect on the relationship between patent citations and market value. When the patent h-index is less than or equal to the lowest threshold, 4, there is a positive relationship between patent citations and market value. This study indicates that the first regime (where the patent h-index is less than or equal to 4) is optimal, because this is where the extent of the positive relationship between patent citations and market value is the greatest.

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Abstract

As an acceptable proxy for innovative activity, patents have become increasingly important in recent years. Patents and patent citations have been used for construction of technology indicators. This article presents an alternative to other citation-based indicators, i.e., the patent h-index, which is borrowed from bibliometrics. We conduct the analysis on a sample of the world's top 20 firms ranked by total patents granted in the period 1996-2005 from the Derwent Innovations Index in the semiconductor area. We also investigate the relationships between the patent h-index and other three indicators, i.e., patent counts, citation counts, and the mean family size (MFS). The findings show that the patent h-index is indeed an effective indicator for evaluating the technological importance and quality, or impact, for an assignee. In addition, the MFS indicator correlates negatively and not significantly with the patent h-index, which indicates that the social value of a patent is in disagreement with its private value. The two indicators, patent h-index and MFS, both provide an overview of the value of patents, but from two different angles.

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Abstract

Science linkage is a widely used patent bibliometric indicator to measure patent linkage to scientific research based on the frequency of citations to scientific papers within the patent. Science linkage is also regarded as noisy because the subject of patent citation behavior varies from inventors/applicants to examiners. In order to identify and ultimately reduce this noise, we analyzed the different citing motivations of examiners and inventors/applicants. We built 4 hypotheses based upon our study of patent law, the unique economic nature of a patent, and a patent citation's market effect. To test our hypotheses, we conducted an expert survey based on our science linkage calculation in the domain of catalyst from U.S. patent data (2006-2009) over 3 types of citations: self-citation by inventor/applicant, non-self-citation by inventor/applicant, and citation by examiner. According to our results, evaluated by domain experts, we conclude that the non-self-citation by inventor/applicant is quite noisy and cannot indicate science linkage and that self-citation by inventor/applicant, although limited, is more appropriate for understanding science linkage.

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Abstract

Bibliometrics has changed out of all recognition since 1958; becoming established as a field, being taught widely in library and information science schools, and being at the core of a number of science evaluation research groups around the world. This was all made possible by the work of Eugene Garfield and his Science Citation Index. This article reviews the distance that bibliometrics has travelled since 1958 by comparing early bibliometrics with current practice, and by giving an overview of a range of recent developments, such as patent analysis, national research evaluation exercises, visualization techniques, new applications, online citation indexes, and the creation of digital libraries. Webometrics, a modern, fast-growing offshoot of bibliometrics, is reviewed in detail. Finally, future prospects are discussed with regard to both bibliometrics and webometrics.

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Abstract

According to Jean M. Tague-Sutcliffe "informetrics" is "the study of the quantitative aspects of information in any form, not just records or bibliographies, and in any social group, not just scientists" (Tague-Sutcliffe, 1992, 1). Leo Egghe also defines "informetrics" in a very broad sense. "(W)e will use the term' informetrics' as the broad term comprising all-metrics studies related to information science, including bibliometrics (bibliographies, libraries,...), scientometrics (science policy, citation analysis, research evaluation,...), webometrics (metrics of the web, the Internet or other social networks such as citation or collaboration networks), ..." (Egghe, 2005b,1311). According to Concepcion S. Wilson "informetrics" is "the quantitative study of collections of moderatesized units of potentially informative text, directed to the scientific understanding of information processes at the social level" (Wilson, 1999, 211). We should add to Wilson's units of text also digital collections of images, videos, spoken documents and music. Dietmar Wolfram divides "informetrics" into two aspects, "system-based characteristics that arise from the documentary content of IR systems and how they are indexed, and usage-based characteristics that arise how users interact with system content and the system interfaces that provide access to the content" (Wolfram, 2003, 6). We would like to follow Tague-Sutcliffe, Egghe, Wilson and Wolfram (and others, for example Björneborn & Ingwersen, 2004) and call this broad research of empirical information science "informetrics". Informetrics includes therefore all quantitative studies in information science. If a scientist performs scientific investigations empirically, e.g. on information users' behavior, on scientific impact of academic journals, on the development of the patent application activity of a company, on links of Web pages, on the temporal distribution of blog postings discussing a given topic, on availability, recall and precision of retrieval systems, on usability of Web sites, and so on, he or she contributes to informetrics. We see three subject areas in information science in which such quantitative research takes place, - information users and information usage, - evaluation of information systems, - information itself, Following Wolfram's article, we divide his system-based characteristics into the "information itself "-category and the "information system"-category. Figure 1 is a simplistic graph of subjects and research areas of informetrics as an empirical information science.

Source

Information - Wissenschaft und Praxis. 57(2006) H.8, S.385-389

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Abstract

Despite over 10 years of research there is no agreement on the most suitable roles for Webometric indicators in support of research policy and almost no field-based Webometrics. This article partly fills these gaps by analyzing the potential of policy-relevant Webometrics for individual scientific fields with the help of 4 case studies. Although Webometrics cannot provide robust indicators of knowledge flows or research impact, it can provide some evidence of networking and mutual awareness. The scope of Webometrics is also relatively wide, including not only research organizations and firms but also intermediary groups like professional associations, Web portals, and government agencies. Webometrics can, therefore, provide evidence about the research process to compliment peer review, bibliometric, and patent indicators: tracking the early, mainly prepublication development of new fields and research funding initiatives, assessing the role and impact of intermediary organizations and the need for new ones, and monitoring the extent of mutual awareness in particular research areas.

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Abstract

We studied steroid research from 1935 to 1965 that led to the discovery of the contraceptive pill and cortisone. Bibliometric and patent file searches indicate that the Syntex industrial laboratory located in Mexico and the Universidad Nacional Autónoma de México (UNAM) produced about 54% of the relevant papers published in mainstream journals, which in turn generated over 80% of the citations and in the case of Syntex, all industrial patents in the field between 1950 and 1965. This course of events, which was unprecedented at that time in a developing country, was interrupted when Syntex moved its research division to the US, leaving Mexico with a small but productive research group in the chemistry of natural products.

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Abstract

Technology sectors differ in terms of technological complexity. When studying technology and innovation through patent analysis it is well known that similar amounts of technological knowledge can produce different numbers of patented innovation as output. A new multilayered approach to measure the technological value of patents based on ego patent citation networks (PCNs) is developed in this study. The results show that the structural indicators for the ego PCN developed in this contribution can characterize groups of patents and, hence, in an indirect way, the health of companies.

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Abstract

Using the 138,751 patents filed in 2006 under the Patent Cooperation Treaty, co-classification analysis is pursued on the basis of three- and four-digit codes in the International Patent Classification (IPC, 8th ed.). The co-classifications among the patents enable us to analyze and visualize the relations among technologies at different levels of aggregation. The hypothesis that classifications might be considered as the organizers of patents into classes, and therefore that co-classification patterns - more than co-citation patterns - might be useful for mapping, is not corroborated. The classifications hang weakly together, even at the four-digit level; at the country level, more specificity can be made visible. However, countries are not the appropriate units of analysis because patent portfolios are largely similar in many advanced countries in terms of the classes attributed. Instead of classes, one may wish to explore the mapping of title words as a better approach to visualize the intellectual organization of patents.

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Abstract

The last 2 decades have witnessed a dramatic increase in the use of patent citation data in social science research. Facilitated by digitization of the patent data and increasing computing power, a community of practice has grown up that has developed methods for using these data to: measure attributes of innovations such as impact and originality; to trace flows of knowledge across individuals, institutions and regions; and to map innovation networks. The objective of this article is threefold. First, it takes stock of these main uses. Second, it discusses 4 pitfalls associated with patent citation data, related to office, time and technology, examiner, and strategic effects. Third, it highlights gaps in our understanding and offers directions for future research.

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Abstract

The fact that patents are documents highly constrained by law and structured by international treaties make them a unique body of publications for tracing the history and evolution of technology. The distinctiveness of prior art patent citations compared to bibliographic references in the nonpatent literature is discussed. Starting from these observations and using the patent classification scheme as a framework of reference, we have identified a data structure, the "technology footprint," derived from the patents cited as prior art for a selected set of patents. This data structure will provide us with dynamic information about the technological components of the selected set of patents, which represents a technology, company, or inventor. Two case studies are presented in order to illustrate the visualization of the technology footprint: one concerning an inventor-Mr. Engelbart, the inventor of the "computer mouse"-and another concerning the early years of a technology-computerized tomography.

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Abstract

"Thomson Reuters' citation indexes i.e. SCI, SSCI and AHCI are said to be "authoritative". Due to the huge influence of these databases on global academic evaluation of productivity and impact, Terje Tüür-Fröhlich decided to conduct case studies on the data quality of Social Sciences Citation Index (SSCI) records. Tüür-Fröhlich investigated articles from social science and law. The main findings: SSCI records contain tremendous amounts of "trivial errors", not only misspellings and typos as previously mentioned in bibliometrics and scientometrics literature. But Tüür-Fröhlich's research documented fatal errors which have not been mentioned in the scientometrics literature yet at all. Tüür-Fröhlich found more than 80 fatal mutations and mutilations of Pierre Bourdieu (e.g. "Atkinson" or "Pierre, B. and "Pierri, B."). SSCI even generated zombie references (phantom authors and works) by data fields' confusion - a deadly sin for a database producer - as fragments of Patent Laws were indexed as fictional author surnames/initials. Additionally, horrific OCR-errors (e.g. "nuxure" instead of "Nature" as journal title) were identified. Tüür-Fröhlich´s extensive quantitative case study of an article of the Harvard Law Review resulted in a devastating finding: only 1% of all correct references from the original article were indexed by SSCI without any mistake or error. Many scientific communication experts and database providers' believe that errors in databanks are of less importance: There are many errors, yes - but they would counterbalance each other, errors would not result in citation losses and would not bear any effect on retrieval and evaluation outcomes. Terje Tüür-Fröhlich claims the contrary: errors and inconsistencies are not evenly distributed but linked with languages biases and publication cultures."

Type

m

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Abstract

Considers 3 different types of bibliometrics, literature bibliometrics, patent bibliometrics and linkage bibliometrics which may be used to address questions of performance and results in government and national research. Stresses the importance of linkage bibliometrics, looking at citations between patents and scientific papers, its relevance to external criteria and to making clear the contribution on an institution or agency to a nation's technological progress

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Abstract

The delimination of a research field in bibliometric studies presents the problem of the diversity of subject classifications used in the sources of input and output data. Classification of documents according the thematic codes or keywords is the most accurate method, mainly used is specialized bibliographic or patent databases. Classification of journals in disciplines presents lower specifity, and some shortcomings as the change over time of both journals and disciplines and the increasing interdisciplinarity of research. Standardization of subject classifications emerges as an important point in bibliometric studies in order to allow international comparisons, although flexibility is needed to meet the needs of local studies