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Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/756

Title: Approaches to Sequence Similarity Representation
Authors: Sokolov, Artem
Rachkovskij, Dmitri
Keywords: Sequence Similarity
Metric Embeddings
Distributed Representations
Neural Networks
Issue Date: 2006
Publisher: Institute of Information Theories and Applications FOI ITHEA
Abstract: We discuss several approaches to similarity preserving coding of symbol sequences and possible connections of their distributed versions to metric embeddings. Interpreting sequence representation methods with embeddings can help develop an approach to their analysis and may lead to discovering useful properties.
URI: http://hdl.handle.net/10525/756
ISSN: 1313-0463
Appears in Collections:Volume 13 Number 3

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