@inproceedings{c7d86d2a956749399b785423289cb269,
title = "A Method for Detecting Behavior-Based User Profiles in Collaborative Ontology Engineering",
abstract = "Ontology engineering is far from trivial and most collaborative methods and tools start from a prede fined set of rules, stakeholders can have in the ontology engineering process. We, however, believe that the di fferent types of user behavior are a priori not known and depend on the ontology engineering project. The detection of such user profi les based on unsupervised learning allows finding roles and responsibilities along peers in a collaborative setting. In this paper, we present a method for automatic detection of user profi les in a collaborative ontology engineering environment by means of the K-means clustering algorithm only by looking at the type of interactions a user makes. In this paper we use the GOSPL ontology engineering tool and method to demonstrate this method. The data used to demonstrate the method stems from two ontology engineering projects involving respectively 42 and 36 users.",
keywords = "Collaborative Ontology Engineering, User Profiling, Clustering",
author = "{Van Laere}, Sven and Ronald Buyl and Marc Nyssen",
year = "2014",
month = "10",
day = "27",
doi = "10.1007/978-3-662-45563-0_40",
language = "English",
isbn = "978-3-662-45562-3",
volume = "8841",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "657--673",
editor = "Robert Meersman and Herv{\'e} Panetto and Tharam Dillon and Michele Missikoff and Lin Liu and Oscar Pastor and Alfredo Cuzzocrea and Timos Sellis",
booktitle = "On the Move to Meaningful Internet Systems: OTM 2014 Conferences",
}