Efficient BSP/CGM Algorithms for Text Retrieval

D.G. Gavalas, C.G. Konstantopoulos, B.G. Mamalis, and G.E. Pantziou (Greece)


BSP model, CGM model, parallel algorithms, text retrieval, document clustering.


In this paper we present efficient, scalable and portable parallel algorithms written in the Coarse-Grained Multi computer (CGM) and the Bulk Synchronous Parallel (BSP) models for the off-line clustering, the on-line retrieval and the update phases of the text retrieval problem based on the vector space model and using clustering to organize and handle a dynamic document collection. To the best of our knowledge, our parallel retrieval algorithms are the first ones analyzed under specific parallel models, which capture within a few parameters the characteristics of the parallel machine.

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