2005
DOI: 10.1155/2005/317136
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Similarity-Based Clustering Strategy for Mobile Ad Hoc Multimedia Databases

Abstract: Abstract. Multimedia data are becoming popular in wireless ad hoc environments. However, the traditional content-based retrieval techniques are inefficient in ad hoc networks due to the multiple limitations such as node mobility, computation capability, memory space, network bandwidth, and data heterogeneity. To provide an efficient platform for multimedia retrieval, we propose to cluster ad hoc multimedia databases based on their semantic contents, and construct a virtual hierarchical indexing infrastructure … Show more

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Cited by 6 publications
(5 citation statements)
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“…Yang et al [26] used similarity-based clustering strategy for mobile ad hoc multimedia databases aiming to build an efficient platform for multimedia retrieval. The authors used a content-aware clustering scheme based on a semantic-aware framework for data organization.…”
Section: Related Workmentioning
confidence: 99%
“…Yang et al [26] used similarity-based clustering strategy for mobile ad hoc multimedia databases aiming to build an efficient platform for multimedia retrieval. The authors used a content-aware clustering scheme based on a semantic-aware framework for data organization.…”
Section: Related Workmentioning
confidence: 99%
“…Data dissemination and management are important in the context of many mobile systems including publish/subscribe systems. Yang et al [30] present techniques for content-based multimedia retrieval in mobile ad hoc networks. Caching and replication of data have been used in mobile systems to improve system performance and reliability.…”
Section: Publish/subscribe Systems In Mobile Wireless Networkmentioning
confidence: 99%
“…Their characteristics in terms of flexibility and cost have made them the candidate technology for different applications such as rescue and military scenarios [14], information dissemination in vehicular networks [22], multimedia databases [1], or even video communication between peers [18]. However, even after a decade of research efforts, their ease-of-use is still quite low, making it a technology only accessible for experts.…”
Section: Introductionmentioning
confidence: 99%