Prediction of Emerging Technologies Based on Analysis of the U.S. Patent Citation Network

The network of patents connected by citations is an evolving graph, which provides a representation of the innovation process. A patent citing another implies that the cited patent reflects a piece of previously existing knowledge that the citing patent builds upon. A methodology presented here (i) identifies actual clusters of patents: i.e. technological branches, and (ii) gives predictions about the temporal changes of the structure of the clusters. A predictor, called the {citation vector}, is defined for characterizing technological development to show how a patent cited by other patents belongs to various industrial fields. The clustering technique adopted is able to detect the new emerging recombinations, and predicts emerging new technology clusters. The predictive ability of our new method is illustrated on the example of USPTO subcategory 11, Agriculture, Food, Textiles. A cluster of patents is determined based on citation data up to 1991, which shows significant overlap of the class 442 formed at the beginning of 1997. These new tools of predictive analytics could support policy decision making processes in science and technology, and help formulate recommendations for action

A study of patent thickets

Report analysing whether entry of UK enterprises into patenting in a technology area is affected by patent thickets in the technology area

Scanning tunneling microscopy and atomic force microscopy in the characterization of activated graphite electrodes

Sir: To date there have been many methods described to activate carbon electrodes, including electrochemical treatment (1-1 7), laser irradiation (18-21), radio-frequency (RF) plasma (22), and heat treatment (23-26). These methods were developed empirically, and only now is an understanding of parameters controlling surface activity beginning to emerge (20,27). Electrochemical treatment and laser irradiation are particularly attractive treatments because they are relatively inexpensive, are quick, and can be performed without removing the electrode from solution. Activation, common to these procedures, may be attributable to an increase in the exposed edge plane density, which has been associated with faster kinetics (14,20). Copper deposition in conjunction with scanning electron microscopy (SEM) has shown an increase in the density of localized defects on active surfaces (15); an increase in surface activity is associated with an increase in the density of the localized defects (15). Scanning tunneling microscopy (STM), phase detection microscopy, and SEM have also been used to study the effects of electrochemical treatment of highly oriented pyrolytic graphite (HOPG) (13) and glassy carbon (GC) (16,17). These studies have suggested an increase in surface roughness consistent with an increase in the density of exposed edge planes

Explicitly searching for useful inventions: dynamic relatedness and the costs of connecting versus synthesizing

Inventions combine technological features. When features are barely related, burdensomely broad knowledge is required to identify the situations that they share. When features are overly related, burdensomely broad knowledge is required to identify the situations that distinguish them. Thus, according to my first hypothesis, when features are moderately related, the costs of connecting and costs of synthesizing are cumulatively minimized, and the most useful inventions emerge. I also hypothesize that continued experimentation with a specific set of features is likely to lead to the discovery of decreasingly useful inventions; the earlier-identified connections reflect the more common consumer situations. Covering data from all industries, the empirical analysis provides broad support for the first hypothesis. Regressions to test the second hypothesis are inconclusive when examining industry types individually. Yet, this study represents an exploratory investigation, and future research should test refined hypotheses with more sophisticated data, such as that found in literature-based discovery research