This study proposes an approach for visualizing a knowledge structure, the proposed approach creates a three-dimensional ''Research focused parallelship network'', a ''Keyword Co-occurrence Network'', and a two-dimensional knowledge map to facilitate visualization of the knowledge structure created by journal papers from different perspectives. The networks and knowledge maps can be depicted differently by choosing different information as the network actor, e.g. author, institute or country keyword, to reflect knowledge structures in micro-, meso-, and macro-levels, respectively. Technology Foresight is selected as an example to illustrate the method proposed in this study. A total of 556 author keywords contained in 181 Technology Foresight related papers have been analyzed. European countries, China, India and Brazil are located at the core of Technology Foresight research. Quantitative ways of mapping journal papers are investigated in this study to unveil emerging elements as well as to demonstrate dynamics and visualization of knowledge. The quantitative method provided in this paper shows a possible way of visualizing and evaluating knowledge structure; thus a computerized calculation is possible for potential quantitative applications, e.g. R&D resource allocation, research performance evaluation, science map, etc.

No abstract

No abstract

This study aims to obtain global technology evolution by constructing and analyzing patent citation network and patent citation map for the field of electrical conducting polymer nanocomposite. A total of 1421 patents are retrieved from USPTO patent database and patent citation network is established by combing both patent citation and social network analysis. Network properties, e.g. Degree Centrality, Betweenness Centrality, and Closeness Centrality, are calculated for representing several technology evolution mechanisms that first proposed in this study. Also, a distance-based patent citation map is constructed by calculating relative distances and positions of patents in the patent citation network. Quantitative ways of exploring technology evolution are investigated in this study to unveil important or emerging techniques as well as to demonstrate dynamics and visualization of technology evolutions.

This study aims to propose an early precaution method which allows predicting probability of patent infringement as well as evaluating patent value. To obtain the purposes, a large-scale analysis on both litigated patents and non-litigated patents issued between 1976 and 2010 by USPTO are conducted. The holistic scale analysis on the two types of patents (3,878,852 non-litigated patents and 31,992 litigated patents in total) issued by USPTO from 1976 to 2010 has not been conducted in literatures and need to be investigated to allow patent researchers to understand the overall picture of the USPTO patents. Also, by comparing characteristics of all litigated patents to that of non-litigated patents, a precaution method for patent litigation can be obtained. Both litigated patents and non-litigated patents are analyzed to understand the differences between the two types of patents in terms of different variables. It is found that there are statistically significant differences for the two types of patents in the following 11 variables: (1) No. of Assignee, (2) No. of Assignee Country, (3) No. of Inventor, (4) Inventor Country, (5) No. of Patent Reference, (6) No. of Patent Citation Received, (7) No. of IPC, (8) No. of UPC, (9) No. of Claim, (10) No. of Non-Patent Reference, and (11) No. of Foreign Reference. Finally, logistic regression is used for predicting the probability of occurrence of a patent litigation by fitting the 11 characteristics of 3,910,844 USPTO patents to a logistic function curve