Similarity Searching for the Big Data Challenges and Research Objectives

ZEZULA, Pavel. Similarity Searching for the Big Data Challenges and Research Objectives. MOBILE NETWORKS & APPLICATIONS. DORDRECHT: SPRINGER, 2015, vol. 20, No 4, p. 487-496. ISSN 1383-469X. Available from: https://dx.doi.org/10.1007/s11036-014-0547-2.

Basic information

• Original name: Similarity Searching for the Big Data Challenges and Research Objectives
• Authors: ZEZULA, Pavel (203 Czech Republic, guarantor, belonging to the institution).
• Edition: MOBILE NETWORKS & APPLICATIONS, DORDRECHT, SPRINGER, 2015, 1383-469X.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: China
• Confidentiality degree: is not subject to a state or trade secret
• Impact factor: Impact factor: 1.538
• RIV identification code: RIV/00216224:14330/15:00087421
• Organization unit: Faculty of Informatics
• Doi: http://dx.doi.org/10.1007/s11036-014-0547-2
• UT WoS: 000360003900010
• Keywords in English: Big data; Scalability; Information retrieval; Similarity search; Findability; Data outsourcing; Data privacy; Information extraction

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. After explaining the impacts of Big Data on similarity searching and summarizing the state of the art in the search technology, four specific research objectives to tackle the challenges are outlined and discussed. It is believed that effective and efficient processing of raw data for object findability and developing hybrid similarity search structures for multi-modal and privacy-preserving searching are necessary to achieve a scalable similarity search technology able to operate on Big Data.

Links

• GBP103/12/G084, research and development project: Name: Centrum pro multi-modální interpretaci dat velkého rozsahu

Investor: Czech Science Foundation