1. Classification of keywords selected from research articles on physics and development of a quantitative subject access tool
- Author
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Dutta, Bidyarthi, Majumder, Krishnapada, and Sen, B. K.
- Subjects
AA. Library and information science as a field. ,AB. Information theory and library theory. ,IB. Content analysis (A and I, class.) ,ID. Knowledge representation. - Abstract
All research articles begin with a title. Most include an abstract. Several include keywords. All three of these features describe an article’s content in details. The title sends an instant reflection of the central theme of the research topic. The abstract summarizes the content. The keywords indicate the core and allied fields of concern. The researchers and indexers quickly and easily locate particular articles within their areas of interest with the aid of keywords. Keywords hold prime importance in abstracting and indexing services. Keywords play major role in information retrieval function. This paper is based on analysis of 14,221 keywords collected from 2,526 research articles published in three journals, viz. Chaos, Physics of plasmas and Low temperature physics since 2006 to 2012. Out of all these author-assigned keywords, the number of distinct bits obtained was 2571. After collection, the lexically close keywords are identified that form clusters. Several such clusters are found and the composition of keywords in nearly all clusters varies over the said time span. Four indicators have been defined on the basis of fluctuating keyword composition within clusters. The name given to these four indicators are stability index, integrated visibility index, momentary visibility index and potency index respectively. These indicators hold different values for different clusters. The value ranges of them are categorized in five groups, viz. very high, high, medium, low and very low. A new quantitative subject access tool has been proposed on the basis of these indicators, which can predict the probable new and obsolete keywords in any subject domain. The name given to this new tool is keysaurus, i.e. keyword-based-thesaurus.
- Published
- 2013