Efficient word retrieval by means of SOM clustering and PCA

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Abstract

We propose an approach for efficient word retrieval from printed documents belonging to Digital Libraries. The approach combines word image clustering (based on Self Organizing Maps, SOM) with Principal Component Analysis. The combination of these methods allows us to efficiently retrieve the matching words from large documents collections without the need for a direct comparison of the query word with each indexed word. © Springer-Verlag Berlin Heidelberg 2006.

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APA

Marinai, S., Faini, S., Marino, E., & Soda, G. (2006). Efficient word retrieval by means of SOM clustering and PCA. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3872 LNCS, pp. 336–347). https://doi.org/10.1007/11669487_30

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