Title :
Pattern discovery from innovation processes
Author :
Diamantini, Claudia ; Genga, Laura ; Potena, Domenico ; Storti, Emanuele
Author_Institution :
Dipt. di Ing. dell´Inf., Univ. Politec. delle Marche, Ancona, Italy
Abstract :
Innovation management and promotion has become one of the most important topics in the Literature about business and executive decision support. In particular, the relationship between innovation and collaboration, both intra- and inter-organization, is gaining an increasing attention in many works, for example in the Open Innovation research field [2]. Innovation activities, especially those that involve collaboration, are typically not structured; they don´t follow a predefined scheme or procedure and are influenced by multiple factors, for instance the individual behaviour, that makes it difficult to apply classical methods of process analysis. In this paper we describe a methodology to discover significant and recurrent patterns in innovation activities, that can be used to support and improve such kind of processes. To evaluate our approach we conducted a set of experiments on a synthetic dataset, which contains a set of traces of innovation activities generated from some abstract templates, drew with the aim to model the typical ways in which innovation is carried on.
Keywords :
data mining; graph theory; pattern clustering; graph-clustering technique; innovation management; innovation processes; inter-organization; intra-organization; open innovation research field; pattern discovery; process mining; Clustering algorithms; Collaboration; Context; Lattices; Proposals; Technological innovation; clustering; collaboration analysis; open innovation; pattern discovery; process mining;
Conference_Titel :
Collaboration Technologies and Systems (CTS), 2013 International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4673-6403-4
DOI :
10.1109/CTS.2013.6567269