ACM Computing Surveys (CSUR)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Cluster validity methods: part I
ACM SIGMOD Record
A Hybrid Approach t Word Segmentation
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Unsupervised learning of the morphology of a natural language
Computational Linguistics
Implementation of a multi-objective genetic algorithm on word segmentation in modern Greek
ASC '07 Proceedings of The Eleventh IASTED International Conference on Artificial Intelligence and Soft Computing
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This paper presents a hierarchical clustering algorithm aimed at creating groups of stems with similar characteristics. The resulting groups (clusters) are expected to comprise stems belonging to the same inflectional paradigm (e.g. verbs in passive voice) which will aid the creation of a morphological lexicon. A new metric for calculating the distance between the data objects is proposed, that better suits the specific application by addressing problems that may occur due to the limited amount of information from the data. A series of experimental results are also provided, that demonstrate the performance of the algorithm, compare different distance metrics in terms of their effectiveness and assist in choosing appropriate approaches for a number of parameters.