Semantic Distances for Technology Landscape Visualization

This paper presents a novel approach to the visualization and subsequent elucidation of research domains in science and technology. The proposed methodology is based on the use of bibliometrics; i.e., analysis is conducted using information regarding trends and patterns of publication rather than the contents of these publications. In particular, we explore the use of term co-occurence frequencies as an indicator of the semantic closeness between pairs of words or phrases. To demonstrate the utility of this approach, a case study on renewable energy technologies is conducted, where the above techniques are used to visualize the interrelationships within a collection of energy-related keywords. As these are regarded as manifestations of the underlying research topics, we contend that the proposed visualizations can be interpreted as representations of the underlying technology landscape. These techniques have many potential applications, but one interesting challenge in which we are particularly interested is the mapping and subsequent prediction of future developments in the technological fields being studied.The research described in this paper was funded by the Masdar Institute of Science and Technology (MIST)

Measuring Innovation Using Bibliometric Techniques: The Case of Solar Photovoltaic Industry

Paper submitted to the Advancing the Study of Innovation and Globalization in Organizations (ASIGO) Conference in Nurnberg, Germany, May 29-30, 2009In this paper, we use feature extraction and data analysis techniques for the elucidation of patterns and trends in technological innovation. In studying innovation, we focus on the role of public research institutions (research universities and national laboratories) in the development of new industries. More specifically, we are interested in measuring innovation through research collaborations between these institutions and the private sector. The proposed methods are primarily drawn from the field of bibliometrics – i.e. the analysis of information and trends in the publication of text documents, rather than the contents of these documents. In particular, we seek to explore the relationship between joint publication patterns and trends, R&D funding, technology development choices, and the viability and effectiveness of industry-university collaborations. To focus the discussions and to provide concrete examples of their applicability, this study will have an initial emphasis on the solar photovoltaic (PV) sector in the U.S., though the techniques and general approach devised here will be applicable to a broad range of industries, situations, and locations. Our analysis suggests that interesting information and conclusions can be derived from this line of analysis. The results obtained using our data extraction techniques allow us to identify early technology focus in different areas within solar PV technologies, and to determine potential technology pathways, which is critical for innovation policy in the renewable energy domain

Latent Semantic Analysis Applied to Tech Mining

This paper presents an approach to bibliometric analysis in the context of technology mining. Bibliometric analysis refers to the use of publication database statistics, e.g., hit counts relevant to a topic of interest. Technology mining facilitates the identification of a technology’s research landscape. Our contribution to bibliometrics in this context is the use of a technique known as Latent Semantic Analysis (LSA) to reveal the concepts that underlie the terms relevant to a field. Using this technique, we can analyze coherent concepts, rather than individual terms. This can lead to more useful results from our bibliometric analysis. We present results that demonstrate the ability of Latent Semantic Analysis to uncover the concepts underlying sets of key terms, used in a case study on the technologies of renewable energy

A Framework for Technology Forecasting and Visualization

This paper presents a novel framework for supporting the development of well-informed research policies and plans. The proposed methodology is based on the use of bibliometrics; i.e., analysis is conducted using information regarding trends and patterns of publication. Information thus obtained is analyzed to predict probable future developments in the technological fields being studied. While using bibliometric techniques to study science and technology is not a new idea, the proposed approach extends previous studies in a number of important ways. Firstly, instead of being purely exploratory, the focus of our research has been on developing techniques for detecting technologies that are in the early growth phase, characterized by a rapid increase in the number of relevant publications. Secondly, to increase the reliability of the forecasting effort, we propose the use of automatically generated keyword taxonomies, allowing the growth potentials of subordinate technologies to aggregated into the overall potential of larger technology categories. As a demonstration, a proof-of-concept implementation of each component of the framework is presented, and is used to study the domain of renewable energy technologies. Results from this analysis are presented and discussed

Bibliometric Analysis of Distributed Generation

This paper describes the application of data mining techniques for eludicating patterns and trends in technological innovation. Specifically, we focus on the use of bibliometric methods, viz techniques which focus on trends in the publication of text documents rather than the content of these documents. Of particular interest is the relationship between publication patterns, as characterized by term occurrence frequencies, and the underlying technological trends and developments which drive these trends. To focus the discussions and to provide a concrete example of their applicability, a detailed case study focussing on research in the area of Distributed Generation (DG) is also presented; however, the techniques and general approach devised here will be applicable to a broad range of industries, situations, and locations. Our results are promising and indicate that interesting information and conclusions can be derived from this line of analysis. The results obtained using data extraction techniques highlight and present the evolution of DG-related technology focus areas, and their relative importance within this field

Part I - Synthesis of photochromic fulgides Part II - Synthetic studies towards anti-SARS agent AG7088

Ph.DDOCTOR OF PHILOSOPH

Comparison of Generality Based Algorithm Variants for Automatic Taxonomy Generation

We compare a family of algorithms for the automatic generation of taxonomies by adapting the Heymannalgorithm in various ways. The core algorithm determines the generality of terms and iteratively inserts them in a growing taxonomy. Variants of the algorithm are created by altering the way and the frequency, generality of terms is calculated. We analyse the performance and the complexity of the variants combined with a systematic threshold evaluation on a set of seven manually created benchmark sets. As a result, betweenness centrality calculated on unweighted similarity graphs often performs best but requires threshold fine-tuning and is computationally more expensive than closeness centrality. Finally, we show how an entropy-based filter can lead to more precise taxonomies

Towards Better Understanding Cybersecurity: or are Cyberspace and Cyber Space the Same?

Although there are many technology challenges and approaches to attaining cybersecurity, human actions (or inactions) also often pose large risks. There are many reasons, but one problem is whether we all “see the world” the same way. That is, what does “cybersecurity” actually mean – as well as the many related concepts, such as “cyberthreat,” “cybercrime,” etc. Although dictionaries, glossaries, and other sources tell you what words/phrases are supposed to mean (somewhat complicated by the fact that they often contradict each other), they do not tell you how people are actually using them. If we are to have an effective solution, it is important that all the parties understand each other – or, at least, understand that there are different perspectives