Performance in ART1-Like Document Clustering with Variable Similarity Thresholds - MacLeod, Kevin (Proceedings of the Annual Conference of CAIS / Actes du congrès annuel de l’ACSI, 2013)
The availability of effective clusters is crucial to many document retrieval systems. MacLeod's algorithm incorporates ART1-like training with static similarity thresholds to form effective document clusters and is well suited to massively parallel implementations [1]. This paper reports on a study of the effectiveness of clusters formed by the algorithm when several variable threshold functions are. . .