BUDÍKOVÁ, Petra, Michal BATKO, David NOVÁK and Pavel ZEZULA. Inherent Fusion: Towards Scalable Multi-Modal Similarity Search. Journal of Database Management. IGI Global, 2016, vol. 27, No 4, p. 1-23. ISSN 1063-8016. Available from: https://dx.doi.org/10.4018/JDM.2016100101.
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Basic information
Original name Inherent Fusion: Towards Scalable Multi-Modal Similarity Search
Authors BUDÍKOVÁ, Petra (203 Czech Republic, guarantor, belonging to the institution), Michal BATKO (203 Czech Republic, belonging to the institution), David NOVÁK (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition Journal of Database Management, IGI Global, 2016, 1063-8016.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 0.462
RIV identification code RIV/00216224:14330/16:00088723
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.4018/JDM.2016100101
UT WoS 000396491200001
Keywords in English Content-Based Retrieval; Evaluation; Image Retrieval; Late Fusion; Multi-Modal Search; Scalability; Similarity Searching
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. Petra Budíková, Ph.D., učo 66445. Changed: 24/4/2019 09:18.
Abstract
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.
Links
GBP103/12/G084, research and development projectName: Centrum pro multi-modální interpretaci dat velkého rozsahu
Investor: Czech Science Foundation
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