Organization of A Massive Document Collection  

Oleh:

Kohonen, T. ; Salojarvi, J. ; Saarela, A. ; Kaski, S. ; Paatero, V. ; Lagus, K. ; Honkela, J.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 11 no. 3 (2000), page 574-585.
Topik: DOCUMENT; organization; massive document; collection

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Describes the implementation of a system that is able to organize vast document collections according to textual similarities. It is based on the self - organizing map (SOM) algorithm. As the feature vectors for the documents statistical representations of their vocabularies are used. The main goal in our work has been to scale up the SOM algorithm to be able to deal with large amounts of high - dimensional data. In a practical experiment we mapped 6840568 patent abstracts onto a 1002240 - node SOM. As the feature vectors we used 500 - dimensional vectors of stochastic figures obtained as random projections of weighted word histograms.

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