A Self-organizing System for Large-scale Content-based Information Retrieval

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F08%3A00029131" target="_blank" >RIV/00216224:14330/08:00029131 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

A Self-organizing System for Large-scale Content-based Information Retrieval

Popis výsledku v původním jazyce

We propose a self-organizing system for content-based information retrieval which operates in an ordinary peer-to-peer network. The system is universal and allows us to search for various data types, e.g. multimedia, because we use the metric space datamodel. The self-organization of the network is obtained by using the social-network paradigm. The connections among peers in the network are created as social-network relationships formed on the basis of a query-and-answer principle. The knowledge of answers to previous queries is exploited to fast navigate to peers, possibly containing the most relevant answers to new queries. At the same time, a randomized mechanism is used to explore new and unvisited parts of the network to provide sufficient information for future exploitation. The proposed concepts are verified using a network consisting of 2,000 peers containing descriptive features of 10 million images from CoPhIR collection.

Název v anglickém jazyce

A Self-organizing System for Large-scale Content-based Information Retrieval

Popis výsledku anglicky

We propose a self-organizing system for content-based information retrieval which operates in an ordinary peer-to-peer network. The system is universal and allows us to search for various data types, e.g. multimedia, because we use the metric space datamodel. The self-organization of the network is obtained by using the social-network paradigm. The connections among peers in the network are created as social-network relationships formed on the basis of a query-and-answer principle. The knowledge of answers to previous queries is exploited to fast navigate to peers, possibly containing the most relevant answers to new queries. At the same time, a randomized mechanism is used to explore new and unvisited parts of the network to provide sufficient information for future exploitation. The proposed concepts are verified using a network consisting of 2,000 peers containing descriptive features of 10 million images from CoPhIR collection.

Druh

A - Audiovizuální tvorba

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GD102%2F05%2FH050" target="_blank" >GD102/05/H050: Integrovaný přístup k výchově studentů DSP v oblasti paralelních a distribuovaných systémů</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2008

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

ISBN

978-80-7355-082-0

Místo vydání

Brno

Název nakladatele resp. objednatele

Ing. Zdeněk Novotný, CSc.

Verze

MEMICS proceedings

Identifikační číslo nosiče

N/A