• Journal of Information Science Theory and Practice
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• v.1 no.4
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• pp.6-11
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• 2013

It is but a short journey from citation indexing to citation analysis and thence to evaluative bibliometrics. This paper outlines the path and describes how the time-honored practice of affixing bibliographic references to scholarly articles has paved the way for a culture of accounting to establish itself in contemporary academia.

• Journal of the Korean Society for Library and Information Science
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• v.49 no.4
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• pp.99-124
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• 2015

As the improvement of digital technologies increases the use of images from various fields, the domain of image retrieval has evolved and become a growing topic of research in the Library and Information Science field. The purpose of this study is to identify the knowledge structure of the image retrieval domain by using the author co-citation analysis and author bibliographic coupling as analytical tools in order to understand the domain's past and present. The data set for this study is 245 articles with 8,031 cited articles in the field of image retrieval from 1998 to 2013, from the Web of Science citation database. According to the results of author co-citation analysis for the past of the image retrieval domain, our findings demonstrate that the intellectual structure of image retrieval in the LIS field consists of predominantly user-oriented approaches, but also includes some areas influenced by the CBIR area. More specifically, the user-oriented approach contains six specific areas which include image needs, information seeking, image needs and search behavior, image indexing and access, indexing of image collection, and web image search. On the other hand, for CBIR approaches, it contains feature-based image indexing, shape-based indexing, and IR & CBIR. The recent trends of image retrieval based on the results from author bibliographic coupling analysis show that the domain is expanding to emerging areas of medical images, multimedia, ontology- and tag-based indexing which thus reflects a new paradigm of information environment.

• Journal of Information Management
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• v.24 no.1
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• pp.32-57
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• 1993

The purpose of this study is to analyze the intellectual structure of economics field in Korea by author co-citation analysis and to investigate the limitations of author co-citation analysis by a new method, namely, indexing term analysis of citing documents.

• Journal of Information Science Theory and Practice
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• v.6 no.2
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• pp.6-23
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• 2018

Digital Science's Dimensions is envisaged as a next-generation research and discovery platform for more efficient access to cross-referenced scholarly publications, grants, patents, and clinical trials. As a new addition to the growing open citation resources, it offers opportunities that may benefit a wide variety of stakeholders of scientific publications, from researchers and policy makers to the general public. In this article, we explore and demonstrate some of the practical potentials in terms of cascading citation expansions. Given a set of publications, the cascading citation expansion process can be iteratively applied to a set of articles so as to extend the coverage to more and more relevant articles through citation links. Although the conceptual origin can be traced back to Garfield's citation indexing, it has been largely limited, until recently, to the few who have unrestricted access to a citation database that is large enough to sustain such iterative expansions. Building on the open application program interface of Dimensions, we integrate cascading citation expansion functions in CiteSpace and demonstrate how one may benefit from these new capabilities. In conclusion, cascading citation expansion has the potential to improve our understanding of the structure and dynamics of scientific knowledge.

• Archives of Plastic Surgery
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• v.42 no.2
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• pp.109-110
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• 2015

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.174-182
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• 2004

In order to produce information the author usually reference other authors' work. A citation index leads users to papers by citations. Citations lead the user to desired information. In this paper, KSCI(Korea Science Citation Index) which defines the relationships between citing documents and cited documents has been constructed. KSCI System is to solve problems for recursive retrieval in ISI's SCI(Science Citation Index) Path Encoding Indexing technique was used to solve the problems. From the analysis of data, this system has efficiency about 8.98% in the aspect of data storage. In the aspect of retrieval, there was efficiency between citing documents and cited documents, especially there was over 40% of efficiency in the retrieval of cited documents. It is concluded that suggested KSCI system will provide efficient storage and retrieval system.

• Journal of Information Science Theory and Practice
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• v.11 no.4
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• pp.40-50
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• 2023

Research in interdisciplinary fields like biomechanics is published in a variety of journals whose visibility depends on bibliometric indexing that is often driven by citation analysis of bibliometric databases. This study documented variation in publication metrics and research subject categories assigned to 14 biomechanics journals. Authors, citation, and citation rate (CR) were collected for the top 15 cited articles in the journals retrieved from the Google Scholar service. Research subject categories were also extracted for journals from three databases (Dimensions, Journal Citation Reports, and Scopus). Despite the focus on biomechanics for the journals studied, these biomechanics journals have widely varying CR and subject categories assigned to them. There were significant (p=0.001) and meaningful (77-108%) differences in median CR between average, low, and high CR groups of these biomechanics journals. Since CR are primary data used to calculate most journal metrics and there is no one biomechanics subject category, field normalization for journal citation metrics in biomechanics is difficult. Care must be taken to accurately interpret most citation metrics of biomechanics journals as biased proxies of general usage of research, given a specific database, time frame, and area of biomechanics research.

• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.305-321
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• 2007

The purpose of this study is to examine whether the information resources referenced by human indexers during indexing process are effective on Text Categorization. More specifically, information resources from bibliographic information as well as full text information were explored in the context of a typical scientific journal article data set. The experiment results pointed out that information resources such as citation, source title, and title were not significantly different with full text. Whereas keyword was found to be significantly different with full text. The findings of this study identify that information resources referenced by human indexers can be considered good candidates for text categorization for automatic subject term assignment.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.3
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• pp.215-234
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• 2014

The purpose of this study is to investigate whether Google Scholar (GS) can substitute Web of Science (WoS) for those who don't have access to the subscription-based indexing service and if users feel GS is useful for scholarly information. To achieve the research purpose, the study evaluates both quantitative and qualitative aspects of the two databases. The major results through statistical analysis show that GS indexes much more records and citations for LIS journals than WoS(p < .01), but users' feedback about GS is not better than those about WoS.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.63-77
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• 2011

The World Wide Web is a very large distributed digital information space. From its origins in 1991, the web has grown to encompass diverse information resources as personal home pasges, online digital libraries and virtual museums. Some estimates suggest that the web currently includes over 500 billion pages in the deep web. The ability to search and retrieve information from the web efficiently and effectively is an enabling technology for realizing its full potential. With powerful workstations and parallel processing technology, efficiency is not a bottleneck. In fact, some existing search tools sift through gigabyte.syze precompiled web indexes in a fraction of a second. But retrieval effectiveness is a different matter. Current search tools retrieve too many documents, of which only a small fraction are relevant to the user query. Furthermore, the most relevant documents do not nessarily appear at the top of the query output order. Also, current search tools can not retrieve the documents related with retrieved document from gigantic amount of documents. The most important problem for lots of current searching systems is to increase the quality of search. It means to provide related documents or decrease the number of unrelated documents as low as possible in the results of search. For this problem, CiteSeer proposed the ACI (Autonomous Citation Indexing) of the articles on the World Wide Web. A "citation index" indexes the links between articles that researchers make when they cite other articles. Citation indexes are very useful for a number of purposes, including literature search and analysis of the academic literature. For details of this work, references contained in academic articles are used to give credit to previous work in the literature and provide a link between the "citing" and "cited" articles. A citation index indexes the citations that an article makes, linking the articleswith the cited works. Citation indexes were originally designed mainly for information retrieval. The citation links allow navigating the literature in unique ways. Papers can be located independent of language, and words in thetitle, keywords or document. A citation index allows navigation backward in time (the list of cited articles) and forwardin time (which subsequent articles cite the current article?) But CiteSeer can not indexes the links between articles that researchers doesn't make. Because it indexes the links between articles that only researchers make when they cite other articles. Also, CiteSeer is not easy to scalability. Because CiteSeer can not indexes the links between articles that researchers doesn't make. All these problems make us orient for designing more effective search system. This paper shows a method that extracts subject and predicate per each sentence in documents. A document will be changed into the tabular form that extracted predicate checked value of possible subject and object. We make a hierarchical graph of a document using the table and then integrate graphs of documents. The graph of entire documents calculates the area of document as compared with integrated documents. We mark relation among the documents as compared with the area of documents. Also it proposes a method for structural integration of documents that retrieves documents from the graph. It makes that the user can find information easier. We compared the performance of the proposed approaches with lucene search engine using the formulas for ranking. As a result, the F.measure is about 60% and it is better as about 15%.