Science and technology interactions discovered with a new topographic map-based visualization tool
نویسندگان
چکیده
A new tool for discovering and visualizing interactions between scientific publication domains and industrial patent domains is introduced. The tool is applied to a database of the United States patent data (USPTO) from 1980 till 1995 and the Science Citation Index (SCI) bibliographic databases. The core algorithm behind our tool is the kernel-based Maximum Entropy Rule (kMER), a learning scheme for developing topographic maps of formal neurons. The Gaussian kernels that correspond to each neuron are used for constructing a density map on which a hillclimbing algorithm is applied for locating and visualizing clusters in the topographic map. For each set of clustered data, a new topographic map is developed, and so on. A new method is introduced in order to visualize this hierarchical structure into a single condensed cluster map. The procedure is applied to patent and bibliographic data separately in order to build two hierarchical structures: one containing clusters of technology classes and the other clusters of science classes. The two data structures are then merged into a single (pseudo-)colored linkage map, colored by the co-occurrences of patents and the scientific publications referred in them. Various zooming facilities are available for visual inspection. After the linkage map for a particular time period is developed, data from other consecutive time periods can be projected onto the map in order to monitor the evolution of the interactions. Finally, in order to quantify the dynamics of the interaction, structural equation modeling, a causal modeling technique, is applied to the most significant co-occurrences in the linkage map.
منابع مشابه
Landforms identification using neural network-self organizing map and SRTM data
During an 11 days mission in February 2000 the Shuttle Radar Topography Mission (SRTM) collected data over 80% of the Earth's land surface, for all areas between 60 degrees N and 56 degrees S latitude. Since SRTM data became available, many studies utilized them for application in topography and morphometric landscape analysis. Exploiting SRTM data for recognition and extraction of topographic ...
متن کاملA new approach for data visualization problem
Data visualization is the process of transforming data, information, and knowledge into visual form, making use of humans’ natural visual capabilities which reveals relationships in data sets that are not evident from the raw data, by using mathematical techniques to reduce the number of dimensions in the data set while preserving the relevant inherent properties. In this paper, we formulated d...
متن کاملTopographic Visualization of the Internet
In the Internet thousands of Internet Service Providers (ISPs) exchange traffic according to their commercial agreements. ISPs are usually thought as organized in a hierarchy with the most important at the top. The peculiar business model of the Internet make paths that traverse higher levels of the hierarchy more expensive than paths that traverse only lower levels. To visually represent routi...
متن کاملNew peptide based freeze-dried kit [99mTc-HYNIC]-UBI 29-41 as a human specific infection imaging agent
Introduction: Ubiquicidin 29-41 (UBI) is a fragment of the cationic antimicrobial peptide that is present in various species including humans. The purpose of this study was to investigate radiochemical and biological characteristics of [6-hydrazinopyridine-3-carboxylic acid (HYNIC)]-UBI 29-41 designed for the labeling with 99mTc using tricine as coligand....
متن کاملTopo-phylogeny: Visualizing evolutionary relationships on a topographic landscape
Phylogenetic trees are the de facto standard for visualizing evolutionary relationships, but large trees can be difficult to interpret because they require a high cognitive load to identify relationships between multiple operational taxonomic units (OTUs). We present a new tool for displaying phylogenetic relationships as a topographic map in which OTUs autonomously attract or repel one another...
متن کامل