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Analysis of institutional authors

Li, TonghongAuthor

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June 9, 2019
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A scalable approach for content based image retrieval in cloud datacenter

Publicated to: INFORMATION SYSTEMS FRONTIERS. 16 (1): 129-141 - 2014-03-01 16(1), DOI: 10.1007/s10796-013-9467-0

Authors:

Liao, JX; Yang, D; Li, TH; Wang, JY; Qi, Q; Zhu, XM
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Affiliations

Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol - Author
Tech Univ Madrid, Dept Comp Sci - Author

Abstract

The emergence of cloud datacenters enhances the capability of online data storage. Since massive data is stored in datacenters, it is necessary to effectively locate and access interest data in such a distributed system. However, traditional search techniques only allow users to search images over exact-match keywords through a centralized index. These techniques cannot satisfy the requirements of content based image retrieval (CBIR). In this paper, we propose a scalable image retrieval framework which can efficiently support content similarity search and semantic search in the distributed environment. Its key idea is to integrate image feature vectors into distributed hash tables (DHTs) by exploiting the property of locality sensitive hashing (LSH). Thus, images with similar content are most likely gathered into the same node without the knowledge of any global information. For searching semantically close images, the relevance feedback is adopted in our system to overcome the gap between low-level features and high-level features. We show that our approach yields high recall rate with good load balance and only requires a few number of hops.
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Keywords

ChordCloud computingContent based image retrievalFrameworkLocality sensitive hashingPeer-to-peerRelevance feedbackSimilarity queriesSystemsTo-peer networks

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal INFORMATION SYSTEMS FRONTIERS due to its progression and the good impact it has achieved in recent years, according to the agency WoS (JCR), it has become a reference in its field. In the year of publication of the work, 2014, it was in position 63/139, thus managing to position itself as a Q2 (Segundo Cuartil), in the category Computer Science, Information Systems. Notably, the journal is positioned en el Cuartil Q2 para la agencia Scopus (SJR) en la categoría Computer Networks and Communications.

Independientemente del impacto esperado determinado por el canal de difusión, es importante destacar el impacto real observado de la propia aportación.

Según las diferentes agencias de indexación, el número de citas acumuladas por esta publicación hasta la fecha 2026-04-28:

  • WoS: 12
  • Scopus: 14
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Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2026-04-28:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 18 (PlumX).

It is essential to present evidence supporting full alignment with institutional principles and guidelines on Open Science and the Conservation and Dissemination of Intellectual Heritage. A clear example of this is:

  • Assignment of a Handle/URN as an identifier within the deposit in the Institutional Repository: https://oa.upm.es/28920/

As a result of the publication of the work in the institutional repository, statistical usage data has been obtained that reflects its impact. In terms of dissemination, we can state that, as of

  • Views: 371
  • Downloads: 543
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Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: China.

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Awards linked to the item

This work was jointly supported by: (1) the National Basic Research Program of China (No. 2013CB329102); (2) National Natural Science Foundation of China (No. 61372120,61271019, 61101119, 61121001, 61072057, 60902051); (3) PCSIRT (No. IRT1049); (4) MICINN (No. TIN2010-19077); (5) CAM (No. S2009TIC-1692).
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