Literature-related discovery (LRD): Methodology

Kostoff, Ronald N.; Briggs, Michael B.; Solka, Jeffrey L.; Rushenberg, Robert L.

doi:10.1016/j.techfore.2007.11.010

Cited by 55 publications

(41 citation statements)

References 18 publications

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“…Kostoff et al (1997) proposed a database tomography for information retrieval as an analytical system to work with large databases. Kostoff et al (2004Kostoff et al ( , 2008 develop a systematic approach with the aim of identifying disruptive technology roadmaps by using literature-based discovery process. Some more systematic methodological frameworks have also been developed for monitoring technology trends.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…Amongst the most intensively discussed and developed quantitative methods are (1) 'bibliometric/scientometric analysis' (e.g. Chao et al 2007;Chen 2006;Cobo et al 2011;Guo et al 2011;Kajikawa et al 2008;Kostoff et al 2008;Morris et al 2002;Porter and Cunningham 2005;Shibata et al 2008;Smalheiser 2001;Upham and Small 2010); (2) 'patent analysis' (e.g. Abraham and Moitra 2001;Campbell 1983;Corrocher et al 2003;Dereli and Durmusoglu 2009;Kim et al 2009Kim et al , 2008Lee et al 2009Lee et al , 2011Porter and Cunningham 2005;Tseng et al 2007;Wang et al 2010;Yoon and Park 2004).…”

Section: Introductionmentioning

confidence: 99%

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A methodology for technology trend monitoring: the case of semantic technologies

et al. 2016

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This paper introduces a systematic technology trend monitoring (TTM) methodology based on an analysis of bibliometric data. Among the key premises for developing a methodology are: (1) the increasing number of data sources addressing different phases of the STI development, and thus requiring a more holistic and integrated analysis; (2) the need for more customized clustering approaches particularly for the purpose of identifying trends; and (3) augmenting the policy impact of trends through gathering future-oriented intelligence on emerging developments and potential disruptive changes. Thus, the TTM methodology developed combines and jointly analyzes different datasets to gain intelligence to cover different phases of the technological evolution starting from the 'emergence' of a technology towards 'supporting' and 'solution' applications and more 'practical' business and market-oriented uses. Furthermore, the study presents a new algorithm for data clustering in order to overcome the weaknesses of readily available clusterization tools for the purpose of identifying technology trends. The present study places the TTM activities into a wider policy context to make use of the outcomes for the purpose of Science, Technology and Innovation policy formulation, and R&D strategy making processes. The methodology developed is demonstrated in the domain of ''semantic technologies''.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A methodology for technology trend monitoring: the case of semantic technologies

et al. 2016

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“…Kostoff provided a novel method of LBD, namely LRD [5] , in 2008. Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e.,potential discovery) [6] .…”

Section: Literature Related Discovery-lrdmentioning

confidence: 99%

“…Literature-related discovery (LRD) is the linking of two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge (i.e.,potential discovery) [6] . Reference [5] introduced the methodology of LRD. His team used five instances to verify the effective of LRD [7][8] [9][10] [11] .…”

Section: Literature Related Discovery-lrdmentioning

confidence: 99%

“…His team used five instances to verify the effective of LRD [7][8] [9][10] [11] . A credible method of LBD needs multiple literatures with four characters [5] , as follow, (1) These multiple literatures should be complementary for solving the problem. If not unique information of each literature, the problem can't be solved.…”

Section: Literature Related Discovery-lrdmentioning

confidence: 99%

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Literature-Based Knowledge Discovery: The State Of The Art

Liu¹,

Fu²

2012

IJACT

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Literature‐related discovery

Kostoff

Block

Solka³

et al. 2009

Annual Review Info Sci & Tec

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IntroductionDiscovery in science is the generation of novel, interesting, plausible, and intelligible knowledge about the objects of study. Literature-related discovery (LRD) is the linking of two or more concepts that have heretofore not been linked (i.e., disjoint), in order to produce new knowledge (i.e., potential discovery). Two major variants of LRD are: open discovery systems (ODS), where one starts with a problem and generates a potential solution (or vice versa), and closed discovery systems (CDS), where one starts with a problem and a potential solution and generates linking mechanism(s).This chapter reviews the state-of-the-art in ODS LRD only. It examines the major LRD concepts, evaluates each concept in detail from the perspective of discovery capability, and examines the level of potential discovery reported in the literature from each concept's implementation. In the evaluation of potential discovery claimed in the published literature, a vetting process is used that requires both characteristics of ODS LRD to be present in order for potential discovery to be affirmed: concepts are linked that have not been linked previously and novel, interesting, plausible, and intelligible knowledge is produced.The major conclusions are that, until recently, most of the reported ODS LRD techniques 5-3 have not generated discovery and this lack of discovery has hampered the growth of ODS LRD substantially. However, ODS LRD techniques have been developed that allow significantly greater amounts of potential discovery to be generated systematically.Discovery is ascertaining something previously unknown or unrecognized. More formally, "Discovery in science is the generation of novel, interesting, plausible, and intelligible knowledge about the objects of study" (Valdes-Perez, 1999, p. 336). It can result from uncovering previously unknown information, from synthesis of publicly available knowledge whose independent segments have never been combined, and/or through invention. In turn, the discovery could derive from logical exploitation of a knowledge base and/or from spontaneous creativity (e.g., Edisonian discoveries from trial and error) (Kostoff, 2003). Innovation reflects the metamorphosis from present practice to some new, ideally "better" practice. It can be based on existing non-implemented knowledge. It can follow discovery directly or resuscitate dormant discovery that has languished for decades.Literature-related discovery (LRD) is a systematic approach to bridging unconnected disciplines based on text mining procedures. LRD allows potentially radical discovery to be hypothesized using either the technical literature alone, or the literature and its authors.In the LRD context, discovery is linking two or more literature concepts that have heretofore not been linked (i.e., disjoint), in order to produce novel, interesting, plausible, and intelligible knowledge. Thus, simply linking two or more disparate concepts is a necessary, but not sufficient, condition for LRD. In particular, concepts may be disjoint b...

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Literature-related discovery (LRD): Methodology

Cited by 55 publications

References 18 publications

A methodology for technology trend monitoring: the case of semantic technologies

A methodology for technology trend monitoring: the case of semantic technologies

Literature-Based Knowledge Discovery: The State Of The Art

Literature‐related discovery

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