TY  - JOUR
T1  - Grouping of business processes models based on an incremental clustering algorithm using fuzzy similarity and multimodal search
JO  - Expert Systems with Applications
VL  - 67
IS  - 
SP  - 163
EP  - 177
PY  - 2017/1//
T2  - 
AU  - Ordoñez, Armando
AU  - Ordoñez, Hugo
AU  - Corrales, Juan Carlos
AU  - Cobos, Carlos
AU  - Wives, Leandro Krug
AU  - Thom, Lucinéia Heloisa
SN  - 0957-4174
DO  - http://dx.doi.org/10.1016/j.eswa.2016.08.061
UR  - http://www.sciencedirect.com/science/article/pii/S0957417416304602
KW  - Business process
KW  - Multimodal
KW  - Search
KW  - Fuzzy
KW  - Clustering
KW  - Assessment
AB  - Abstract
Nowadays, many companies standardize their operations through Business Process (BP), which are stored in repositories and reused when new functionalities are required. However, finding specific processes may become a cumbersome task due to the large size of these repositories. This paper presents MulTimodalGroup, a model for grouping and searching business processes. The grouping mechanism is built upon a clustering algorithm that uses a similarity function based on fuzzy logic; this grouping is performed using the results of each user request. By its part, the search is based on a multimodal representation that integrates textual and structural information of BP. The assessment of the proposed model was carried out in two phases: 1) internal quality assessment of groups and 2) external assessment of the created groups compared with an ideal set of groups. The assessment was performed using a closed BP collection designed collaboratively by 59 experts. The experimental results in each phase are promising and evidence the validity of the proposed model.
ER  -