Abstract not found

This paper presents a new map representing the structure of all of science, based on journal articles, including both the natural and social sciences. Similar to cartographic maps of our world, the map of science provides a bird’s eye view of today’s scientific landscape. It can be used to visually identify major areas of science, their size, similarity, and interconnectedness. In order to be useful, the map needs to be accurate on a local and on a global scale. While our recent work has focused on the former aspect, 1 this paper summarizes results on how to achieve structural accuracy. Eight alternative measures of journal similarity were applied to a data set of 7,121 journals covering over 1 million documents in the combined Science Citation and Social Science Citation Indexes. For each journal similarity measure we generated two-dimensional spatial layouts using the force-directed graph layout tool, VxOrd. Next, mutual information values were calculated for each graph at different clustering levels to give a measure of structural accuracy for each map. The best co-citation and inter-citation maps according to local and structural accuracy were selected and are presented and characterized. These two maps are compared to establish robustness. The inter-citation map is then used to examine linkages between disciplines. Biochemistry appears as the most interdisciplinary discipline in science.

In this article, we define webometrics within the framework of informetric studies and bibliometrics, as belonging to library and information science, and as associated with cybermetrics as a generic subfield. We develop a consistent and detailed link typology and terminology and make explicit the distinction among different Web node levels when using the proposed conceptual framework. As a consequence, we propose a novel diagram notation to fully appreciate and investigate link structures between Web nodes in webometric analyses. We warn against taking the analogy between citation analyses and link analyses too far.

This chapter introduces Semantic Association Networks (SANs), a novel means of using semantic web technology to tag and interlink scientific datasets, services (e.g., algorithms, techniques, or approaches), publications (e.g., papers, patents, grants), and expertise (i.e., author and user information) to improve scholarly knowledge and expertise management. Among other ends, the proposed SANs

The old Asian legend about the blind men and the elephant comes to mind when looking at how different authors of scientific papers describe a piece of related prior work. It turns out that different citations to the same paper often focus on different aspects of that paper and that neither provides a full description of its full set of contributions. In this paper we will describe our investigation of this phenomenon. We studied citation summaries in the context of research papers in the biomed-ical domain. A citation summary is the set of citing sentences for a given article and can be used as a surrogate for the actual article in a variety of scenarios. It contains information that was deemed by peers to be important. Our study shows that citation summaries overlap to some extent with the abstracts of the papers and that they also differ from them in that they focus on different aspects of these papers than the abstracts do. In addition to this, co-cited articles (which are pairs of articles cited by another article) tend to be similar. We show results based on a lexical similarity metric called cohesion to justify our claims. 1 1

Although time has been recognized as an important dimension in the co-citation literature, to date it has not been incorporated into the analogous process of link analysis on the Web. In this paper, we discuss several aspects and uses of the time dimension in the context of Web information retrieval. We describe the ideal case— where search engines track and store temporal data for each of the pages in their repository, assigning timestamps to the hyperlinks embedded within the pages. We introduce several applications which benefit from the availability of such timestamps. To demonstrate our claims, we use a somewhat simplistic approach, which dates links by approximating the age of the page’s content. We show that by using this crude measure alone it is possible to detect and expose significant events and trends. We predict that by using more robust methods for tracking modifications in the content of pages, search engines will be able to provide results that are more timely and better reflect current real-life trends than those they provide today.

We propose the use of the text of the sentences surrounding citations as an important tool for semantic interpretation of bioscience text. We hypothesize several di#erent uses of citation sentences (which we call citances), including the creation of training and testing data for semantic analysis (especially for entity and relation recognition), synonym set creation, database curation, document summarization, and information retrieval generally. We illustrate some of these ideas, showing that citations to one document in particular align well with what a hand-built curator extracted. We also show preliminary results on the problem of normalizing the di#erent ways that the same concepts are expressed within a set of citances, using and improving on existing techniques in automatic paraphrase generation.

method of locating potentially relevant articles on a given subject by identifying subsequent articles that cite a previously published article. An important feature of Google Scholar is that researchers can use it to trace interconnections among authors citing articles on the same topic and to determine the frequency with which others cite a specific article, as it has a “cited by " feature. This study begins with Background of the study Eugene Garfield first outlined the idea of a unified citation index to the literature of science in 1955. “Citation indexes resolve semantic problems associated with traditional subject indexes by using citation symbology rather than words to describe the content of a document ” (Weinstock 1971). Eugene Garfield’s main purpose in proposing the construction of a citation index for science, in which the references in scientific articles are used as index terms, was for the citation index to function as an information retrieval tool for scientific information (Garfield 1955). The rationale behind this kind of indexing is to exploit what Garfield calls the “association-of-ideas ” or “Citations are the formal, explicit linkages between papers that have particular points in common ” (Garfield 1979, 1). Soon after the beginning of the World Wide Web, the literature available on the Web increased very rapidly. The growing amount of literature on the Web and the need for multidisciplinary information retrieval accentuated the need for improved retrieval methods because while the documents were readily available, locating them

Nanoscale science and engineering (NSE) and related areas have seen rapid growth in recent years. The speed and scope of development in the field have made it essential for researchers to be informed on the progress across different laboratories, companies, industries and countries. In this project, we experimented with several analysis and visualization techniques on NSE-related United States patent documents to support various knowledge tasks. This paper presents results on the basic analysis of nanotechnology patents between 1976 and 2002, content map analysis and citation network analysis. The data have been obtained on individual countries, institutions and technology fields. The top 10 countries with the largest number of nanotechnology patents are the United States, Japan, France, the United Kingdom, Taiwan, Korea, the Netherlands, Switzerland, Italy and Australia. The fastest growth in the last 5 years has been in chemical and pharmaceutical fields, followed by semiconductor devices. The results demonstrate potential of information-based discovery and visualization technologies to capture knowledge regarding nanotechnology performance, transfer of knowledge and trends of development through analyzing the patent documents.

Background Researchers turn to citation tracking to find the most influential articles for a particular topic, and to see how often their own published papers are cited. For years researchers looking for this type of information had only one resource to consult: the Web of Science. In 2004, two competitors emerged – Scopus and Google Scholar. The research reported here uses citation analysis in an observational study examining these three databases; comparing citation counts for articles from two disciplines (oncology and condensed matter physics) and two years (1993 and 2003). Methods 11 journal titles with varying impact factors were selected from each discipline (oncology and condensed matter physics) using the Journal Citation Reports (JCR). All articles published in the selected titles were retrieved for both years, and a stratified random sample of articles was chosen, resulting in four sets of articles. During the week of November 7-12, 2005 we extracted the citation counts for each research article from the three sources. The actual citing references for a subset of the articles published in 2003 were also gathered from each of the three sources.