Mining Goal Refinement Patterns: Distilling Know-How from Data View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017-10-21

AUTHORS

Metta Santiputri , Novarun Deb , Muhammad Asjad Khan , Aditya Ghose , Hoa Dam , Nabendu Chaki

ABSTRACT

Goal models play an important role by providing a hierarchic representation of stakeholder intent, and by providing a representation of lower-level subgoals that must be achieved to enable the achievement of higher-level goals. A goal model can be viewed as a composition of a number of goal refinement patterns that relate parent goals to subgoals. In this paper, we offer a means for mining these patterns from enterprise event logs and a technique to leverage vector representations of words and phrases to compose these patterns to obtain complete goal models. The resulting machinery can be quiote powerful in its ability to mine know-how or constitutive norms. We offer an empirical evaluation using both real-life and synthetic datasets. More... »

PAGES

69-76

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-69904-2_6

DOI

http://dx.doi.org/10.1007/978-3-319-69904-2_6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1092370110


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