Research Papers: Design Informatics

Mention and Focus Organism Detection and Their Applications for Scalable Systematic Bio-Ideation Tools

[+] Author and Article Information
Dennis Vandevenne

Department of Mechanical Engineering,
KU Leuven,
Celestijnenlaan 300A,
Leuven 3001, Belgium
e-mail: Dennis.Vandevenne@kuleuven.be

Paul-Armand Verhaegen

Department of Mechanical Engineering,
KU Leuven,
Celestijnenlaan 300A,
Leuven 3001, Belgium
e-mail: PaulArmand.Verhaegen@kuleuven.be

R. Joost Duflou

Department of Mechanical Engineering,
KU Leuven,
Celestijnenlaan 300A,
Leuven 3001, Belgium
e-mail: Joost.Duflou@kuleuven.be

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received January 15, 2014; final manuscript received August 8, 2014; published online October 8, 2014. Assoc. Editor: Ashok K. Goel.

J. Mech. Des 136(11), 111104 (Oct 08, 2014) (8 pages) Paper No: MD-14-1043; doi: 10.1115/1.4028278 History: Received January 15, 2014; Revised August 08, 2014

More and more approaches for systematic biologically inspired design (BID) aim to scalably leverage large biological databases. To support the scalable systematic BID process, an automated method for mention and focus organism (FO) detection in biological strategy documents is proposed and validated to perform with 85% precision and 81% recall. Furthermore, a number of potential applications of mention and FO detection are presented, and the biodiversity of two corpora is measured.

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Grahic Jump Location
Fig. 1

FO detection and biodiversity measurement

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Fig. 2

Characterization of geckos performed by SEABIRD

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Fig. 3

Measured biodiversity of the JEB at the (super) kingdom level

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Fig. 4

Measured biodiversity of the JEB at the class level (The top ten classes for FOs, representing 71% of the corpus, are shown)

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Fig. 5

Measured biodiversity of the AskNature corpus at the (super) kingdom level



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