A structure-based clustering on LDAP directory information

Authors:
Vassiliki Koutsonikola;Athena Vakali;Antonios Mpalasas;Michael Valavanis
Affiliations:
Department of Informatics, Aristotle University, Thessaloniki, Greece;Department of Informatics, Aristotle University, Thessaloniki, Greece;Department of Informatics, Aristotle University, Thessaloniki, Greece;Department of Informatics, Aristotle University, Thessaloniki, Greece
Venue:
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
Year:
2008

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Abstract

LDAP directories have rapidly emerged as the essential framework for storing a wide range of heterogeneous information under various applications and services. Increasing amounts of information are being stored in LDAP directories imposing the need for efficient data organization and retrieval. In this paper, we propose the LPAIR & LMERGE (LP-LM) hierarchical agglomerative clustering algorithm for improving LDAP data organization. LP-LM merges a pair of clusters at each step, considering the LD-vectors, which represent the entries' structure. The clustering-based LDAP data organization enhances LDAP server's response times, under a specific query framework.