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A study on Similarity analysis of National R&D Programs using R&D Project's technical classification
Author(s) -
Ju-ho Kim,
Young-Ja Kim,
Jong-Bae Kim
Publication year - 2012
Publication title -
journal of digital contents society
Language(s) - English
Resource type - Journals
eISSN - 2287-738X
pISSN - 1598-2009
DOI - 10.9728/dcs.2012.13.3.317
Subject(s) - similarity (geometry) , cosine similarity , nearest neighbor search , reliability (semiconductor) , computer science , information retrieval , euclidean distance , data mining , mathematics , artificial intelligence , pattern recognition (psychology) , image (mathematics) , physics , power (physics) , quantum mechanics
Recently, coordination task of similarity between national R&D programs is emphasized on view from the R&D investment efficiency. But the previous similarity search method like text-based similarity search which using keyword of R&D projects has reached the limit due to deviation of document`s quality. For the solve the limitations of text-based similarity search using the keyword extraction, in this study, utilization of R&D project`s technical classification will be discussed as a new similarity search method when analyzed of similarity between national R&D programs. To this end, extracts the Science and Technology Standard Classification of R & D projects which are collected when national R&D Survey & analysis, and creates peculiar vector model of each R&D programs. Verify a reliability of this study by calculate the cosine-based and Euclidean distance-based similarity and compare with calculated the text-based similarity.

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