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@article{1374148,
author = {Budíková, Petra and Batko, Michal and Novák, David and Zezula, Pavel},
article_number = {4},
doi = {http://dx.doi.org/10.4018/JDM.2016100101},
keywords = {Content-Based Retrieval; Evaluation; Image Retrieval; Late Fusion; Multi-Modal Search; Scalability; Similarity Searching},
language = {eng},
issn = {1063-8016},
journal = {Journal of Database Management},
title = {Inherent Fusion: Towards Scalable Multi-Modal Similarity Search},
volume = {27},
year = {2016}
}
TY - JOUR
ID - 1374148
AU - Budíková, Petra - Batko, Michal - Novák, David - Zezula, Pavel
PY - 2016
TI - Inherent Fusion: Towards Scalable Multi-Modal Similarity Search
JF - Journal of Database Management
VL - 27
IS - 4
SP - 1-23
EP - 1-23
PB - IGI Global
SN - 10638016
KW - Content-Based Retrieval
KW - Evaluation
KW - Image Retrieval
KW - Late Fusion
KW - Multi-Modal Search
KW - Scalability
KW - Similarity Searching
N2 - 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.
ER -
BUDÍKOVÁ, Petra, Michal BATKO, David NOVÁK a Pavel ZEZULA. Inherent Fusion: Towards Scalable Multi-Modal Similarity Search. \textit{Journal of Database Management}. IGI Global, 2016, roč.~27, č.~4, s.~1-23. ISSN~1063-8016. Dostupné z: https://dx.doi.org/10.4018/JDM.2016100101.
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