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Type: Artigo de evento
Title: Hamming Dht: Taming The Similarity Search
Author: Da Silva Villaca R.
De Paula L.B.
Pasquini R.
Magalhaes M.F.
Abstract: The semantic meaning of a content is frequently represented by content vectors in which each dimension represents an attribute of this content, such as, keywords in a text, colors in a picture or profile information in a social network. However, one important challenge in this semantic context is the storage and retrieval of similar contents, such as the search for similar images assisting a medical procedure. Based on it, this paper presents a new Distributed Hash Table (DHT), called Hamming DHT, in which Locality Sensitive Hashing (LSH) functions, specially the Random Hyperplane Hashing (RHH), are used to generate content identifiers, propitiating a scenario in which similar contents are stored in peers nearly located in the indexing space of the proposed DHT. The evaluations of this work simulate profiles in a social network to verify if the proposed DHT is capable of reducing the number of hops required in order to improve the recall in the context of a similarity search. © 2013 IEEE.
Rights: fechado
Identifier DOI: 10.1109/CCNC.2013.6488418
Date Issue: 2013
Appears in Collections:Unicamp - Artigos e Outros Documentos

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