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Authors: Omar Ali 1 ; Giovanni Zappella 2 ; Tijl De Bie 1 and Nello Cristianini 1

Affiliations: 1 Bristol University, United Kingdom ; 2 Università Degli Studi di Milano, Italy

Keyword(s): Nodes classification, Social networks, Data mining, Machine learning.

Related Ontology Subjects/Areas/Topics: Applications ; Artificial Intelligence ; Data Engineering ; Information Retrieval ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Missing Data ; Natural Language Processing ; On-Line Learning ; Ontologies and the Semantic Web ; Pattern Recognition ; Software Engineering ; Symbolic Systems ; Theory and Methods

Abstract: The task of predicting the label of a network node, based on the labels of the remaining nodes, is an area of growing interest in machine learning, as various types of data are naturally represented as nodes in a graph. As an increasing number of methods and approaches are proposed to solve this task, the problem of comparing their performance becomes of key importance. In this paper we present an extensive experimental comparison of 15 different methods, on 15 different labelled-networks, as well as releasing all datasets and source code. In addition, we release a further set of networks that were not used in this study (as not all benchmarked methods could manage very large datasets). Besides the release of data, protocols and algorithms, the key contribution of this study is that in each of the 225 combinations we tested, the best performance—both in accuracy and running time—was achieved by the same algorithm: Online Majority Vote. This is also one of the simplest methods to impl ement. (More)

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Paper citation in several formats:
Ali, O.; Zappella, G.; De Bie, T. and Cristianini, N. (2012). AN EMPIRICAL COMPARISON OF LABEL PREDICTION ALGORITHMS ON AUTOMATICALLY INFERRED NETWORKS. In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-8425-99-7; ISSN 2184-4313, SciTePress, pages 259-268. DOI: 10.5220/0003695702590268

@conference{icpram12,
author={Omar Ali. and Giovanni Zappella. and Tijl {De Bie}. and Nello Cristianini.},
title={AN EMPIRICAL COMPARISON OF LABEL PREDICTION ALGORITHMS ON AUTOMATICALLY INFERRED NETWORKS},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2012},
pages={259-268},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003695702590268},
isbn={978-989-8425-99-7},
issn={2184-4313},
}

TY - CONF

JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - AN EMPIRICAL COMPARISON OF LABEL PREDICTION ALGORITHMS ON AUTOMATICALLY INFERRED NETWORKS
SN - 978-989-8425-99-7
IS - 2184-4313
AU - Ali, O.
AU - Zappella, G.
AU - De Bie, T.
AU - Cristianini, N.
PY - 2012
SP - 259
EP - 268
DO - 10.5220/0003695702590268
PB - SciTePress