ZEZULA, Pavel. Scalable Similarity Search for Big Data - Challenges and Research Objectives. In Jason J. Jung, Costin Badica, and Attila Kiss. Scalable Information Systems - 5th International Conference. Berlin: Springer, 2015, p. 3-12. ISBN 978-3-319-16867-8. Available from: https://dx.doi.org/10.1007/978-3-319-16868-5_1.
Other formats:   BibTeX LaTeX RIS
Basic information
Original name Scalable Similarity Search for Big Data - Challenges and Research Objectives
Name in Czech Škálovatelné podobnostní hledání pro BigData - výzvy a výzkumné cíle
Authors ZEZULA, Pavel (203 Czech Republic, guarantor, belonging to the institution).
Edition Berlin, Scalable Information Systems - 5th International Conference, p. 3-12, 10 pp. 2015.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Germany
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14330/15:00080758
Organization unit Faculty of Informatics
ISBN 978-3-319-16867-8
ISSN 1867-8211
Doi http://dx.doi.org/10.1007/978-3-319-16868-5_1
Keywords (in Czech) podobnostní hledání; škálovatelnost; velká data; výzvy
Keywords in English similarity search; scalability; big data; chllenges
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 27/8/2019 11:56.
Abstract
Analysis of contemporary Big Data collections require an effective and efficient content-based access to data which is usually unstructured. This first implies a necessity to uncover descriptive knowledge of complex and heterogeneous objects to make them findable. Second, multimodal search structures are needed to efficiently execute complex similarity queries possibly in outsourced environments while preserving privacy. Four specific research objectives to tackle the challenges are outlined and discussed. It is believed that a relevant solution of these problems is necessary for a scalable similarity search operating on Big Data.
Abstract (in Czech)
Analýza současných velkých data požaduje efektivní přístup k údajům pomocí obsahu. To v prvé řadě vyžaduje techniky extrakce specifického obsahu a dále organizační struktury pro podobnostní hledání. Čtyři základní výzvy jsou definovány za účelem vyřešení problému v prostředí velkých dat.
Links
GBP103/12/G084, research and development projectName: Centrum pro multi-modální interpretaci dat velkého rozsahu
Investor: Czech Science Foundation
PrintDisplayed: 25/4/2024 13:58