Information coupling in web databases

Web information coupling refers to an association of topically related web documents. This coupling is initiated explicitly by a user in a web warehouse specially designed for web information. Web information coupling provides the means to derive additional, useful information from the WWW. In this paper, we discuss and show how two web operators, i.e., global web coupling and local web coupling , are used to associate related web information from the WWW and also from multiple web tables in a web warehouse. This paper discusses various issues in web coupling such as coupling semantics, coupling-compability, and coupling evaluation. 1 Introduction Given the high rate of growth of the volume of data available on the WWW, locating information of interest in such an anarchic setting becomes a more difficult task everyday. Thus, there is the recognition of the undeferring need for effective and efficient tools for information consumers, who must be able to easily locate and manipulate inf..

WEDAGEN: A synthetic web database generator

To improve searching and processing of information on the web, a web warehousing system called WHOWEDA is being developed at the Centre for Advanced Information Systems (CAIS). This system incorporates a Web Information Coupling Model that describes the web objects and their relationships and a web algebra consisting of web operators to manipulate the web objects. In order to measure the performance of WHOWEDA and similar systems that manipulate web information, a synthetic web database generator called WEDAGEN (WEb DAtabase GENerator) has been developed. It has the capability of generating web databases of different sizes and complexities determined by a set of user specified parameters. This paper presents the issues in the design and implementation of WEDAGEN. It also gives a detailed description of its system components and the strategy to generate synthetic web databases. A preliminary assessment of the use of WEDAGEN has been reported. 1 Introduction 1.1 Background The Wold Wi..

Large-Scale Analysis of the Accuracy of the Journal Classification Systems of Web of Science and Scopus

Journal classification systems play an important role in bibliometric analyses. The two most important bibliographic databases, Web of Science and Scopus, each provide a journal classification system. However, no study has systematically investigated the accuracy of these classification systems. To examine and compare the accuracy of journal classification systems, we define two criteria on the basis of direct citation relations between journals and categories. We use Criterion I to select journals that have weak connections with their assigned categories, and we use Criterion II to identify journals that are not assigned to categories with which they have strong connections. If a journal satisfies either of the two criteria, we conclude that its assignment to categories may be questionable. Accordingly, we identify all journals with questionable classifications in Web of Science and Scopus. Furthermore, we perform a more in-depth analysis for the field of Library and Information Science to assess whether our proposed criteria are appropriate and whether they yield meaningful results. It turns out that according to our citation-based criteria Web of Science performs significantly better than Scopus in terms of the accuracy of its journal classification system

Software tools for conducting bibliometric analysis in science: An up-to-date review

Bibliometrics has become an essential tool for assessing and analyzing the output of scientists, cooperation between universities, the effect of state-owned science funding on national research and development performance and educational efficiency, among other applications. Therefore, professionals and scientists need a range of theoretical and practical tools to measure experimental data. This review aims to provide an up-to-date review of the various tools available for conducting bibliometric and scientometric analyses, including the sources of data acquisition, performance analysis and visualization tools. The included tools were divided into three categories: general bibliometric and performance analysis, science mapping analysis, and libraries; a description of all of them is provided. A comparative analysis of the database sources support, pre-processing capabilities, analysis and visualization options were also provided in order to facilitate its understanding. Although there are numerous bibliometric databases to obtain data for bibliometric and scientometric analysis, they have been developed for a different purpose. The number of exportable records is between 500 and 50,000 and the coverage of the different science fields is unequal in each database. Concerning the analyzed tools, Bibliometrix contains the more extensive set of techniques and suitable for practitioners through Biblioshiny. VOSviewer has a fantastic visualization and is capable of loading and exporting information from many sources. SciMAT is the tool with a powerful pre-processing and export capability. In views of the variability of features, the users need to decide the desired analysis output and chose the option that better fits into their aims

Development of Computer Science Disciplines - A Social Network Analysis Approach

In contrast to many other scientific disciplines, computer science considers conference publications. Conferences have the advantage of providing fast publication of papers and of bringing researchers together to present and discuss the paper with peers. Previous work on knowledge mapping focused on the map of all sciences or a particular domain based on ISI published JCR (Journal Citation Report). Although this data covers most of important journals, it lacks computer science conference and workshop proceedings. That results in an imprecise and incomplete analysis of the computer science knowledge. This paper presents an analysis on the computer science knowledge network constructed from all types of publications, aiming at providing a complete view of computer science research. Based on the combination of two important digital libraries (DBLP and CiteSeerX), we study the knowledge network created at journal/conference level using citation linkage, to identify the development of sub-disciplines. We investigate the collaborative and citation behavior of journals/conferences by analyzing the properties of their co-authorship and citation subgraphs. The paper draws several important conclusions. First, conferences constitute social structures that shape the computer science knowledge. Second, computer science is becoming more interdisciplinary. Third, experts are the key success factor for sustainability of journals/conferences