Applied Informetrics for Digital Libraries: An Overview of Foundations, Problems and Current Approaches

Schaer, Philipp Applied Informetrics for Digital Libraries: An Overview of Foundations, Problems and Current Approaches. Historical Social Research, 2013, vol. 38, n. 3, pp. 267-281. [Journal article (Paginated)]

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English abstract

The foundation of every research project is a comprehensive literature review. The search for scientific literature in information systems is a discipline at the intersection of information retrieval and digital libraries; recent user studies in both fields show two typical weaknesses of the classical IR approach: ranking of retrieved and maybe relevant documents and the language problem during the query formulation phase. At the same time the performance of traditional retrieval systems that rely primarily on textual document and query features have been stagnating for years, as could be observed in IR evaluation campaigns such as TREC or CLEF. Therefore alternative approaches to surpass these two problem fields are needed. Recent developments in the area of applied informetrics show very promising effects by using long-known informetric and bibliometric methods like the analysis of power-law distributions described by Lotka's, Zipf's or Bradford's laws, or the application of co-occurrences analysis for entities like authors, journals or references of scientific literature. This work will concentrate on the description of the open problems and the current approaches to surpass these by using applied informetrics methodologies.

Item type:	Journal article (Paginated)
Keywords:	Digital libraries, informetrics, Power Law, Bradford's Law, Lotka's Law, Zipf's Law, information retrieval, co-occurrence analysis
Subjects:	A. Theoretical and general aspects of libraries and information. > AB. Information theory and library theory. A. Theoretical and general aspects of libraries and information. > AC. Relationship of LIS with other fields . L. Information technology and library technology > LM. Automatic text retrieval. L. Information technology and library technology > LS. Search engines.
Depositing user:	Philipp Schaer
Date deposited:	24 Feb 2014 11:46
Last modified:	02 Oct 2014 12:30
URI:	http://hdl.handle.net/10760/22630

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