Inherent Fusion: Towards Scalable Multi-Modal Similarity Search

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F16%3A00088723" target="_blank" >RIV/00216224:14330/16:00088723 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.4018/JDM.2016100101" target="_blank" >http://dx.doi.org/10.4018/JDM.2016100101</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.4018/JDM.2016100101" target="_blank" >10.4018/JDM.2016100101</a>

Result language
angličtina
Original language name
Inherent Fusion: Towards Scalable Multi-Modal Similarity Search
Original language description
The rapid growth of unstructured data, commonly denoted as the Big Data challenge, requires new technologies that are capable of dealing with complex data objects such as multimedia. In this work, the authors focus on the content-based retrieval approach, which is able to organize such data by exploiting the similarity of data content. In particular, they focus on solutions that are able to combine multiple similarity measures during the query evaluation. The authors introduce a classification of existing approaches and analyze their performance in terms of effectiveness, efficiency, and scalability. Further, they present a novel technique of inherent fusion that combines the efficiency of fast indexed retrieval with the effectiveness of ranking methods. The performance of all discussed methods is evaluated by extensive experiments with user participation.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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