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Analyzing website content for improved R&T collaboration planning

: Thorleuchter, Dirk; Poel, Dirk van den

Preprint urn:nbn:de:0011-n-2646932 (262 KByte PDF)
MD5 Fingerprint: e6fa58b8167d8356b922bdead8f18add
Created on: 12.8.2014

Rocha, Á. ; Asociación Ibérica de Sistemas y Tecnologías de Información -AISTI-:
Advances in information systems and technologies : The 2013 World Conference on Information Systems and Technologies (WorldCIST´13); 27th-30th of March in Olhão, Algarve, Portugal
Berlin: Springer, 2013 (Advances in Intelligent Systems and Computing 206)
ISBN: 3-642-36980-4
ISBN: 978-3-642-36980-3 (Print)
ISBN: 978-3-642-36981-0 (Online)
World Conference on Information Systems and Technologies (WorldCIST) <2013, Olhão/Portugal>
Conference Paper, Electronic Publication
Fraunhofer INT ()
collaboration; research; technology; semantic classification; text mining; defense

A well-known problem in research and technology (R&T) planning is the selection of suited R&T collaboration partners. We investigate the use of textual information from the website content of possible collaboration candidates to identify their suitability. This improves the selection of collaboration partners and it enables a successful processing of R&T-projects. In a case study 'defense R&T', organizations and companies that have proven their suitability as collaboration partner in former R&T projects are selected (positive examples) as well as organizations and companies that have not. Latent semantic indexing with singular value decomposition and logistic regression modeling is used to identify semantic textual patterns from their websites' content. As a result of prediction modeling, some of these textual patterns are successful in predicting new organizations or companies as (un-) suited R&T collaboration partners. These results support the acquisition of new coll aboration partners and thus, they are valuable for the planning of R&T.