Experiments with a Sparse Distributed Memory for Text Classification  

Oleh:

Mendes, Mateus ; Coimbra, A. Paulo ; Crisostomo, Manuel M. ; Rodrigues, Jorge

Jenis: Article from Books - E-Book
Dalam koleksi: Transactions on Engineering Technologies: Special Volume of the World Congress on Engineering 2013, page 555-568.
Topik: SDM; Sparse distributed memory; Text classification; Text comparison; Long range correlations; Vector space model
Fulltext: 40_978-94-017-8831-1_Mendes_Coimbra_Crisostomo.pdf (401.12KB)

Isi artikel

The Sparse Distributed Memory (SDM) has been studied for decades as a theoretical model of an associative memory in many aspects similar to the human brain. It has been tested for different purposes. The present work describes its use as a quick text classifier, based on pattern similarity only. The results found with different datasets were superior to the performance of the dumb classifier or purely random choice, even without text preprocessing. Experiments were performed with a popular Reuters newsgroups dataset and also for real time web ad serving.

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